Overview

Dataset statistics

Number of variables35
Number of observations6125498
Missing cells13933909
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 GiB
Average record size in memory273.0 B

Variable types

Numeric5
Categorical26
Unsupported3
Boolean1

Alerts

Unit ID has a high cardinality: 970 distinct valuesHigh cardinality
Call Date has a high cardinality: 8339 distinct valuesHigh cardinality
Watch Date has a high cardinality: 8339 distinct valuesHigh cardinality
Received DtTm has a high cardinality: 2810229 distinct valuesHigh cardinality
Entry DtTm has a high cardinality: 2810768 distinct valuesHigh cardinality
Dispatch DtTm has a high cardinality: 3126518 distinct valuesHigh cardinality
Response DtTm has a high cardinality: 5620807 distinct valuesHigh cardinality
On Scene DtTm has a high cardinality: 4717666 distinct valuesHigh cardinality
Transport DtTm has a high cardinality: 1605017 distinct valuesHigh cardinality
Hospital DtTm has a high cardinality: 1468126 distinct valuesHigh cardinality
Available DtTm has a high cardinality: 5704138 distinct valuesHigh cardinality
Address has a high cardinality: 34050 distinct valuesHigh cardinality
RowID has a high cardinality: 6125498 distinct valuesHigh cardinality
case_location has a high cardinality: 107102 distinct valuesHigh cardinality
Call Number is highly overall correlated with Incident NumberHigh correlation
Incident Number is highly overall correlated with Call NumberHigh correlation
Zipcode of Incident is highly overall correlated with Battalion and 2 other fieldsHigh correlation
Analysis Neighborhoods is highly overall correlated with Neighborhooods - Analysis BoundariesHigh correlation
Call Type is highly overall correlated with Call Type GroupHigh correlation
Call Final Disposition is highly overall correlated with Call Type GroupHigh correlation
Battalion is highly overall correlated with Zipcode of Incident and 2 other fieldsHigh correlation
Original Priority is highly overall correlated with Priority and 1 other fieldsHigh correlation
Priority is highly overall correlated with Original Priority and 1 other fieldsHigh correlation
Final Priority is highly overall correlated with Original Priority and 2 other fieldsHigh correlation
ALS Unit is highly overall correlated with Unit TypeHigh correlation
Call Type Group is highly overall correlated with Call Type and 2 other fieldsHigh correlation
Unit Type is highly overall correlated with ALS UnitHigh correlation
Fire Prevention District is highly overall correlated with Zipcode of Incident and 2 other fieldsHigh correlation
Neighborhooods - Analysis Boundaries is highly overall correlated with Zipcode of Incident and 3 other fieldsHigh correlation
Call Type is highly imbalanced (63.8%)Imbalance
City is highly imbalanced (75.6%)Imbalance
Original Priority is highly imbalanced (57.1%)Imbalance
Priority is highly imbalanced (63.9%)Imbalance
Number of Alarms is highly imbalanced (98.4%)Imbalance
Response DtTm has 435276 (7.1%) missing valuesMissing
On Scene DtTm has 1358394 (22.2%) missing valuesMissing
Transport DtTm has 4518068 (73.8%) missing valuesMissing
Hospital DtTm has 4655157 (76.0%) missing valuesMissing
Available DtTm has 77143 (1.3%) missing valuesMissing
Call Type Group has 2818694 (46.0%) missing valuesMissing
Response DtTm is uniformly distributedUniform
On Scene DtTm is uniformly distributedUniform
Transport DtTm is uniformly distributedUniform
Hospital DtTm is uniformly distributedUniform
Available DtTm is uniformly distributedUniform
RowID is uniformly distributedUniform
RowID has unique valuesUnique
Station Area is an unsupported type, check if it needs cleaning or further analysisUnsupported
Box is an unsupported type, check if it needs cleaning or further analysisUnsupported
Supervisor District is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-02-22 04:13:11.797913
Analysis finished2023-02-22 04:28:12.783535
Duration15 minutes and 0.99 seconds
Software versionydata-profiling vv4.0.0
Download configurationconfig.json

Variables

Call Number
Real number (ℝ)

Distinct2816812
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2185973 × 108
Minimum1030101
Maximum2.305202 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 MiB
2023-02-21T23:28:13.027699image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1030101
5-th percentile12440309
Q163390285
median1.2357037 × 108
Q31.8067362 × 108
95-th percentile2.2077256 × 108
Maximum2.305202 × 108
Range2.294901 × 108
Interquartile range (IQR)1.1728333 × 108

Descriptive statistics

Standard deviation65673537
Coefficient of variation (CV)0.53892732
Kurtosis-1.1639249
Mean1.2185973 × 108
Median Absolute Deviation (MAD)57310672
Skewness-0.15738029
Sum7.4645153 × 1014
Variance4.3130135 × 1015
MonotonicityNot monotonic
2023-02-21T23:28:13.121450image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202931462 104
 
< 0.1%
202100407 98
 
< 0.1%
161701875 83
 
< 0.1%
113560168 79
 
< 0.1%
140700278 79
 
< 0.1%
202940499 77
 
< 0.1%
92420136 74
 
< 0.1%
201440320 72
 
< 0.1%
150283120 71
 
< 0.1%
122860052 66
 
< 0.1%
Other values (2816802) 6124695
> 99.9%
ValueCountFrequency (%)
1030101 2
< 0.1%
1030104 2
< 0.1%
1030106 1
 
< 0.1%
1030107 3
< 0.1%
1030108 2
< 0.1%
1030112 1
 
< 0.1%
1030113 1
 
< 0.1%
1030116 1
 
< 0.1%
1030117 3
< 0.1%
1030118 2
< 0.1%
ValueCountFrequency (%)
230520197 2
< 0.1%
230520195 3
< 0.1%
230520190 1
 
< 0.1%
230520177 2
< 0.1%
230520172 2
< 0.1%
230520164 4
< 0.1%
230520163 1
 
< 0.1%
230520154 3
< 0.1%
230520153 4
< 0.1%
230520152 2
< 0.1%

Unit ID
Categorical

Distinct970
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
E03
 
196608
E01
 
188906
E36
 
131553
T03
 
98509
E07
 
96829
Other values (965)
5413093 

Length

Max length6
Median length3
Mean length2.8776836
Min length2

Characters and Unicode

Total characters17627245
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)< 0.1%

Sample

1st rowE36
2nd rowE29
3rd rowT07
4th rowB02
5th rowE41

Common Values

ValueCountFrequency (%)
E03 196608
 
3.2%
E01 188906
 
3.1%
E36 131553
 
2.1%
T03 98509
 
1.6%
E07 96829
 
1.6%
E05 82901
 
1.4%
E06 75977
 
1.2%
RC1 75748
 
1.2%
E08 75099
 
1.2%
E13 74855
 
1.2%
Other values (960) 5028513
82.1%

Length

2023-02-21T23:28:13.231173image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
e03 196608
 
3.2%
e01 188906
 
3.1%
e36 131553
 
2.1%
t03 98509
 
1.6%
e07 96829
 
1.6%
e05 82901
 
1.4%
e06 75977
 
1.2%
rc1 75748
 
1.2%
e08 75099
 
1.2%
e13 74855
 
1.2%
Other values (960) 5028513
82.1%

Most occurring characters

ValueCountFrequency (%)
E 2288851
13.0%
0 2227582
12.6%
1 2223159
12.6%
3 1444172
 
8.2%
2 1146814
 
6.5%
8 967085
 
5.5%
M 949867
 
5.4%
6 872644
 
5.0%
7 829222
 
4.7%
4 820673
 
4.7%
Other values (27) 3857176
21.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11893189
67.5%
Uppercase Letter 5734050
32.5%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2288851
39.9%
M 949867
16.6%
T 676980
 
11.8%
B 412910
 
7.2%
R 405379
 
7.1%
K 242935
 
4.2%
C 237877
 
4.1%
A 218820
 
3.8%
S 148782
 
2.6%
D 43291
 
0.8%
Other values (15) 108358
 
1.9%
Decimal Number
ValueCountFrequency (%)
0 2227582
18.7%
1 2223159
18.7%
3 1444172
12.1%
2 1146814
9.6%
8 967085
8.1%
6 872644
 
7.3%
7 829222
 
7.0%
4 820673
 
6.9%
5 790683
 
6.6%
9 571155
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
p 3
50.0%
x 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11893189
67.5%
Latin 5734056
32.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2288851
39.9%
M 949867
16.6%
T 676980
 
11.8%
B 412910
 
7.2%
R 405379
 
7.1%
K 242935
 
4.2%
C 237877
 
4.1%
A 218820
 
3.8%
S 148782
 
2.6%
D 43291
 
0.8%
Other values (17) 108364
 
1.9%
Common
ValueCountFrequency (%)
0 2227582
18.7%
1 2223159
18.7%
3 1444172
12.1%
2 1146814
9.6%
8 967085
8.1%
6 872644
 
7.3%
7 829222
 
7.0%
4 820673
 
6.9%
5 790683
 
6.6%
9 571155
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17627245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 2288851
13.0%
0 2227582
12.6%
1 2223159
12.6%
3 1444172
 
8.2%
2 1146814
 
6.5%
8 967085
 
5.5%
M 949867
 
5.4%
6 872644
 
5.0%
7 829222
 
4.7%
4 820673
 
4.7%
Other values (27) 3857176
21.9%

Incident Number
Real number (ℝ)

Distinct2816812
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12066811
Minimum30612
Maximum23024964
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 MiB
2023-02-21T23:28:13.356272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum30612
5-th percentile1075292.9
Q16095644.2
median12119676
Q318028782
95-th percentile22035623
Maximum23024964
Range22994352
Interquartile range (IQR)11933138

Descriptive statistics

Standard deviation6579255.2
Coefficient of variation (CV)0.5452356
Kurtosis-1.1637967
Mean12066811
Median Absolute Deviation (MAD)5917682
Skewness-0.15647227
Sum7.3915229 × 1013
Variance4.3286599 × 1013
MonotonicityNot monotonic
2023-02-21T23:28:13.465662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120587 104
 
< 0.1%
20086100 98
 
< 0.1%
16067026 83
 
< 0.1%
11118181 79
 
< 0.1%
14023691 79
 
< 0.1%
20120882 77
 
< 0.1%
9071789 74
 
< 0.1%
20059798 72
 
< 0.1%
15010877 71
 
< 0.1%
12094502 66
 
< 0.1%
Other values (2816802) 6124695
> 99.9%
ValueCountFrequency (%)
30612 2
< 0.1%
30614 1
 
< 0.1%
30615 3
< 0.1%
30616 2
< 0.1%
30620 1
 
< 0.1%
30621 1
 
< 0.1%
30624 1
 
< 0.1%
30625 2
< 0.1%
30626 3
< 0.1%
30627 3
< 0.1%
ValueCountFrequency (%)
23024964 2
< 0.1%
23024963 3
< 0.1%
23024962 1
 
< 0.1%
23024961 2
< 0.1%
23024960 2
< 0.1%
23024959 4
< 0.1%
23024958 1
 
< 0.1%
23024957 3
< 0.1%
23024956 4
< 0.1%
23024955 2
< 0.1%

Call Type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
Medical Incident
4025272 
Structure Fire
715178 
Alarms
679552 
Traffic Collision
 
248503
Other
 
102400
Other values (28)
 
354593

Length

Max length44
Median length16
Mean length14.768468
Min length5

Characters and Unicode

Total characters90464222
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOutside Fire
2nd rowAlarms
3rd rowAlarms
4th rowAlarms
5th rowAlarms

Common Values

ValueCountFrequency (%)
Medical Incident 4025272
65.7%
Structure Fire 715178
 
11.7%
Alarms 679552
 
11.1%
Traffic Collision 248503
 
4.1%
Other 102400
 
1.7%
Citizen Assist / Service Call 91240
 
1.5%
Outside Fire 79652
 
1.3%
Water Rescue 32400
 
0.5%
Gas Leak (Natural and LP Gases) 27705
 
0.5%
Vehicle Fire 27485
 
0.4%
Other values (23) 96111
 
1.6%

Length

2023-02-21T23:28:13.560516image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
incident 4026912
33.7%
medical 4025272
33.7%
fire 825981
 
6.9%
structure 718985
 
6.0%
alarms 679552
 
5.7%
traffic 248503
 
2.1%
collision 248503
 
2.1%
128566
 
1.1%
other 102400
 
0.9%
outside 94132
 
0.8%
Other values (55) 847233
 
7.1%

Most occurring characters

ValueCountFrequency (%)
e 10418938
11.5%
i 10204189
11.3%
c 9263393
10.2%
n 8529844
9.4%
d 8219794
9.1%
t 6021131
 
6.7%
5820541
 
6.4%
l 5552559
 
6.1%
a 5407367
 
6.0%
I 4044111
 
4.5%
Other values (38) 16982355
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 72584819
80.2%
Uppercase Letter 11817551
 
13.1%
Space Separator 5820541
 
6.4%
Other Punctuation 129451
 
0.1%
Close Punctuation 55930
 
0.1%
Open Punctuation 55930
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10418938
14.4%
i 10204189
14.1%
c 9263393
12.8%
n 8529844
11.8%
d 8219794
11.3%
t 6021131
8.3%
l 5552559
7.6%
a 5407367
7.4%
r 3563380
 
4.9%
u 1625549
 
2.2%
Other values (13) 3778675
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
I 4044111
34.2%
M 4031558
34.1%
S 849038
 
7.2%
F 832769
 
7.0%
A 780523
 
6.6%
C 432449
 
3.7%
T 250227
 
2.1%
O 210473
 
1.8%
E 60301
 
0.5%
L 55419
 
0.5%
Other values (10) 270683
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 128566
99.3%
, 885
 
0.7%
Space Separator
ValueCountFrequency (%)
5820541
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55930
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55930
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 84402370
93.3%
Common 6061852
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10418938
12.3%
i 10204189
12.1%
c 9263393
11.0%
n 8529844
10.1%
d 8219794
9.7%
t 6021131
7.1%
l 5552559
6.6%
a 5407367
6.4%
I 4044111
 
4.8%
M 4031558
 
4.8%
Other values (33) 12709486
15.1%
Common
ValueCountFrequency (%)
5820541
96.0%
/ 128566
 
2.1%
) 55930
 
0.9%
( 55930
 
0.9%
, 885
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90464222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 10418938
11.5%
i 10204189
11.3%
c 9263393
10.2%
n 8529844
9.4%
d 8219794
9.1%
t 6021131
 
6.7%
5820541
 
6.4%
l 5552559
 
6.1%
a 5407367
 
6.0%
I 4044111
 
4.5%
Other values (38) 16982355
18.8%

Call Date
Categorical

Distinct8339
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
09/02/2017
 
1741
09/01/2017
 
1725
10/24/2021
 
1570
06/10/2019
 
1414
01/01/2012
 
1362
Other values (8334)
6117686 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters61254980
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05/01/2022
2nd row01/19/2022
3rd row05/03/2021
4th row10/20/2021
5th row04/30/2022

Common Values

ValueCountFrequency (%)
09/02/2017 1741
 
< 0.1%
09/01/2017 1725
 
< 0.1%
10/24/2021 1570
 
< 0.1%
06/10/2019 1414
 
< 0.1%
01/01/2012 1362
 
< 0.1%
06/14/2000 1307
 
< 0.1%
10/19/2022 1264
 
< 0.1%
12/31/2022 1245
 
< 0.1%
01/04/2008 1232
 
< 0.1%
12/17/2021 1229
 
< 0.1%
Other values (8329) 6111409
99.8%

Length

2023-02-21T23:28:13.638638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
09/02/2017 1741
 
< 0.1%
09/01/2017 1725
 
< 0.1%
10/24/2021 1570
 
< 0.1%
06/10/2019 1414
 
< 0.1%
01/01/2012 1362
 
< 0.1%
06/14/2000 1307
 
< 0.1%
10/19/2022 1264
 
< 0.1%
12/31/2022 1245
 
< 0.1%
01/04/2008 1232
 
< 0.1%
12/17/2021 1229
 
< 0.1%
Other values (8329) 6111409
99.8%

Most occurring characters

ValueCountFrequency (%)
0 16607916
27.1%
/ 12250996
20.0%
2 11494356
18.8%
1 9038676
14.8%
3 1965933
 
3.2%
8 1677675
 
2.7%
9 1663030
 
2.7%
7 1658617
 
2.7%
6 1648656
 
2.7%
5 1647223
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49003984
80.0%
Other Punctuation 12250996
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16607916
33.9%
2 11494356
23.5%
1 9038676
18.4%
3 1965933
 
4.0%
8 1677675
 
3.4%
9 1663030
 
3.4%
7 1658617
 
3.4%
6 1648656
 
3.4%
5 1647223
 
3.4%
4 1601902
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/ 12250996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61254980
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16607916
27.1%
/ 12250996
20.0%
2 11494356
18.8%
1 9038676
14.8%
3 1965933
 
3.2%
8 1677675
 
2.7%
9 1663030
 
2.7%
7 1658617
 
2.7%
6 1648656
 
2.7%
5 1647223
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61254980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16607916
27.1%
/ 12250996
20.0%
2 11494356
18.8%
1 9038676
14.8%
3 1965933
 
3.2%
8 1677675
 
2.7%
9 1663030
 
2.7%
7 1658617
 
2.7%
6 1648656
 
2.7%
5 1647223
 
2.7%

Watch Date
Categorical

Distinct8339
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
09/01/2017
 
1826
09/02/2017
 
1755
10/24/2021
 
1478
12/31/2014
 
1407
12/31/2022
 
1392
Other values (8334)
6117640 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters61254980
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row04/30/2022
2nd row01/18/2022
3rd row05/03/2021
4th row10/20/2021
5th row04/30/2022

Common Values

ValueCountFrequency (%)
09/01/2017 1826
 
< 0.1%
09/02/2017 1755
 
< 0.1%
10/24/2021 1478
 
< 0.1%
12/31/2014 1407
 
< 0.1%
12/31/2022 1392
 
< 0.1%
06/10/2019 1385
 
< 0.1%
06/14/2000 1271
 
< 0.1%
12/31/2019 1251
 
< 0.1%
12/31/2013 1240
 
< 0.1%
09/13/2019 1234
 
< 0.1%
Other values (8329) 6111259
99.8%

Length

2023-02-21T23:28:17.712768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
09/01/2017 1826
 
< 0.1%
09/02/2017 1755
 
< 0.1%
10/24/2021 1478
 
< 0.1%
12/31/2014 1407
 
< 0.1%
12/31/2022 1392
 
< 0.1%
06/10/2019 1385
 
< 0.1%
06/14/2000 1271
 
< 0.1%
12/31/2019 1251
 
< 0.1%
12/31/2013 1240
 
< 0.1%
09/13/2019 1234
 
< 0.1%
Other values (8329) 6111259
99.8%

Most occurring characters

ValueCountFrequency (%)
0 16597374
27.1%
/ 12250996
20.0%
2 11501412
18.8%
1 9037805
14.8%
3 1972572
 
3.2%
8 1677185
 
2.7%
9 1661417
 
2.7%
7 1659082
 
2.7%
6 1648781
 
2.7%
5 1645178
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49003984
80.0%
Other Punctuation 12250996
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16597374
33.9%
2 11501412
23.5%
1 9037805
18.4%
3 1972572
 
4.0%
8 1677185
 
3.4%
9 1661417
 
3.4%
7 1659082
 
3.4%
6 1648781
 
3.4%
5 1645178
 
3.4%
4 1603178
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/ 12250996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61254980
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16597374
27.1%
/ 12250996
20.0%
2 11501412
18.8%
1 9037805
14.8%
3 1972572
 
3.2%
8 1677185
 
2.7%
9 1661417
 
2.7%
7 1659082
 
2.7%
6 1648781
 
2.7%
5 1645178
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61254980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16597374
27.1%
/ 12250996
20.0%
2 11501412
18.8%
1 9037805
14.8%
3 1972572
 
3.2%
8 1677185
 
2.7%
9 1661417
 
2.7%
7 1659082
 
2.7%
6 1648781
 
2.7%
5 1645178
 
2.7%

Received DtTm
Categorical

Distinct2810229
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
10/19/2020 12:28:08 PM
 
104
07/28/2020 06:40:26 AM
 
98
06/18/2016 02:19:13 PM
 
83
12/22/2011 11:52:54 AM
 
79
03/11/2014 04:55:27 PM
 
79
Other values (2810224)
6125055 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters134760956
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique889051 ?
Unique (%)14.5%

Sample

1st row05/01/2022 02:58:25 AM
2nd row01/19/2022 01:42:12 AM
3rd row05/03/2021 09:28:12 PM
4th row10/20/2021 10:08:47 PM
5th row04/30/2022 06:35:58 PM

Common Values

ValueCountFrequency (%)
10/19/2020 12:28:08 PM 104
 
< 0.1%
07/28/2020 06:40:26 AM 98
 
< 0.1%
06/18/2016 02:19:13 PM 83
 
< 0.1%
12/22/2011 11:52:54 AM 79
 
< 0.1%
03/11/2014 04:55:27 PM 79
 
< 0.1%
10/20/2020 07:25:33 AM 77
 
< 0.1%
08/30/2009 10:45:34 AM 74
 
< 0.1%
05/23/2020 04:11:30 AM 72
 
< 0.1%
01/28/2015 06:44:43 PM 71
 
< 0.1%
05/04/2011 05:34:14 PM 66
 
< 0.1%
Other values (2810219) 6124695
> 99.9%

Length

2023-02-21T23:28:17.985232image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 3719352
 
20.2%
am 2406146
 
13.1%
09/02/2017 1741
 
< 0.1%
09/01/2017 1725
 
< 0.1%
10/24/2021 1570
 
< 0.1%
06/10/2019 1414
 
< 0.1%
01/01/2012 1362
 
< 0.1%
06/14/2000 1307
 
< 0.1%
10/19/2022 1264
 
< 0.1%
12/31/2022 1245
 
< 0.1%
Other values (51531) 12239368
66.6%

Most occurring characters

ValueCountFrequency (%)
0 24928281
18.5%
2 15807308
11.7%
1 15032715
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5709526
 
4.2%
5 5354424
 
4.0%
4 5323570
 
4.0%
Other values (6) 19726646
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85756972
63.6%
Other Punctuation 24501992
 
18.2%
Space Separator 12250996
 
9.1%
Uppercase Letter 12250996
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24928281
29.1%
2 15807308
18.4%
1 15032715
17.5%
3 5709526
 
6.7%
5 5354424
 
6.2%
4 5323570
 
6.2%
9 3447368
 
4.0%
8 3433650
 
4.0%
7 3380229
 
3.9%
6 3339901
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 6125498
50.0%
P 3719352
30.4%
A 2406146
 
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 12250996
50.0%
: 12250996
50.0%
Space Separator
ValueCountFrequency (%)
12250996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122509960
90.9%
Latin 12250996
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24928281
20.3%
2 15807308
12.9%
1 15032715
12.3%
/ 12250996
10.0%
12250996
10.0%
: 12250996
10.0%
3 5709526
 
4.7%
5 5354424
 
4.4%
4 5323570
 
4.3%
9 3447368
 
2.8%
Other values (3) 10153780
8.3%
Latin
ValueCountFrequency (%)
M 6125498
50.0%
P 3719352
30.4%
A 2406146
 
19.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134760956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24928281
18.5%
2 15807308
11.7%
1 15032715
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5709526
 
4.2%
5 5354424
 
4.0%
4 5323570
 
4.0%
Other values (6) 19726646
14.6%

Entry DtTm
Categorical

Distinct2810768
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
10/19/2020 12:28:08 PM
 
104
07/28/2020 06:41:51 AM
 
98
06/18/2016 02:19:40 PM
 
83
12/22/2011 11:53:42 AM
 
79
03/11/2014 04:56:24 PM
 
79
Other values (2810763)
6125055 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters134760956
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique889006 ?
Unique (%)14.5%

Sample

1st row05/01/2022 02:59:15 AM
2nd row01/19/2022 01:44:13 AM
3rd row05/03/2021 09:28:12 PM
4th row10/20/2021 10:09:53 PM
5th row04/30/2022 06:37:28 PM

Common Values

ValueCountFrequency (%)
10/19/2020 12:28:08 PM 104
 
< 0.1%
07/28/2020 06:41:51 AM 98
 
< 0.1%
06/18/2016 02:19:40 PM 83
 
< 0.1%
12/22/2011 11:53:42 AM 79
 
< 0.1%
03/11/2014 04:56:24 PM 79
 
< 0.1%
10/20/2020 07:25:33 AM 77
 
< 0.1%
08/30/2009 10:46:49 AM 74
 
< 0.1%
05/23/2020 04:12:17 AM 72
 
< 0.1%
01/28/2015 06:45:42 PM 71
 
< 0.1%
10/02/2006 02:09:01 PM 67
 
< 0.1%
Other values (2810758) 6124694
> 99.9%

Length

2023-02-21T23:28:18.271306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 3722359
 
20.3%
am 2403139
 
13.1%
09/02/2017 1739
 
< 0.1%
09/01/2017 1725
 
< 0.1%
10/24/2021 1571
 
< 0.1%
06/10/2019 1414
 
< 0.1%
01/01/2012 1360
 
< 0.1%
06/14/2000 1303
 
< 0.1%
10/19/2022 1261
 
< 0.1%
12/31/2022 1245
 
< 0.1%
Other values (51531) 12239378
66.6%

Most occurring characters

ValueCountFrequency (%)
0 24915699
18.5%
2 15803386
11.7%
1 15030855
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5707942
 
4.2%
5 5361243
 
4.0%
4 5330547
 
4.0%
Other values (6) 19732798
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85756972
63.6%
Other Punctuation 24501992
 
18.2%
Space Separator 12250996
 
9.1%
Uppercase Letter 12250996
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24915699
29.1%
2 15803386
18.4%
1 15030855
17.5%
3 5707942
 
6.7%
5 5361243
 
6.3%
4 5330547
 
6.2%
9 3446537
 
4.0%
8 3436973
 
4.0%
7 3378752
 
3.9%
6 3345038
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 6125498
50.0%
P 3722359
30.4%
A 2403139
 
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 12250996
50.0%
: 12250996
50.0%
Space Separator
ValueCountFrequency (%)
12250996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122509960
90.9%
Latin 12250996
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24915699
20.3%
2 15803386
12.9%
1 15030855
12.3%
/ 12250996
10.0%
12250996
10.0%
: 12250996
10.0%
3 5707942
 
4.7%
5 5361243
 
4.4%
4 5330547
 
4.4%
9 3446537
 
2.8%
Other values (3) 10160763
8.3%
Latin
ValueCountFrequency (%)
M 6125498
50.0%
P 3722359
30.4%
A 2403139
 
19.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134760956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24915699
18.5%
2 15803386
11.7%
1 15030855
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5707942
 
4.2%
5 5361243
 
4.0%
4 5330547
 
4.0%
Other values (6) 19732798
14.6%

Dispatch DtTm
Categorical

Distinct3126518
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
12/22/2011 11:54:25 AM
 
79
08/30/2009 10:47:01 AM
 
74
10/12/2012 04:40:53 AM
 
66
05/04/2011 05:36:36 PM
 
66
03/16/2002 11:50:22 PM
 
65
Other values (3126513)
6125148 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters134760956
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1290201 ?
Unique (%)21.1%

Sample

1st row05/01/2022 02:59:25 AM
2nd row01/19/2022 01:44:28 AM
3rd row05/03/2021 09:28:17 PM
4th row10/20/2021 10:10:07 PM
5th row04/30/2022 06:37:43 PM

Common Values

ValueCountFrequency (%)
12/22/2011 11:54:25 AM 79
 
< 0.1%
08/30/2009 10:47:01 AM 74
 
< 0.1%
10/12/2012 04:40:53 AM 66
 
< 0.1%
05/04/2011 05:36:36 PM 66
 
< 0.1%
03/16/2002 11:50:22 PM 65
 
< 0.1%
10/02/2006 02:09:24 PM 64
 
< 0.1%
07/08/2005 02:35:25 AM 63
 
< 0.1%
10/20/2010 05:06:47 AM 62
 
< 0.1%
06/20/2012 01:51:00 PM 60
 
< 0.1%
05/06/2012 09:50:15 AM 59
 
< 0.1%
Other values (3126508) 6124840
> 99.9%

Length

2023-02-21T23:28:18.624404image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 3725204
 
20.3%
am 2400294
 
13.1%
09/02/2017 1738
 
< 0.1%
09/01/2017 1725
 
< 0.1%
10/24/2021 1578
 
< 0.1%
06/10/2019 1414
 
< 0.1%
01/01/2012 1363
 
< 0.1%
06/14/2000 1302
 
< 0.1%
10/19/2022 1260
 
< 0.1%
12/31/2022 1247
 
< 0.1%
Other values (51532) 12239369
66.6%

Most occurring characters

ValueCountFrequency (%)
0 24915274
18.5%
2 15800587
11.7%
1 15029854
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5716494
 
4.2%
5 5362871
 
4.0%
4 5329705
 
4.0%
Other values (6) 19727685
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85756972
63.6%
Other Punctuation 24501992
 
18.2%
Space Separator 12250996
 
9.1%
Uppercase Letter 12250996
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24915274
29.1%
2 15800587
18.4%
1 15029854
17.5%
3 5716494
 
6.7%
5 5362871
 
6.3%
4 5329705
 
6.2%
9 3443016
 
4.0%
8 3433539
 
4.0%
7 3382124
 
3.9%
6 3343508
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 6125498
50.0%
P 3725204
30.4%
A 2400294
 
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 12250996
50.0%
: 12250996
50.0%
Space Separator
ValueCountFrequency (%)
12250996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122509960
90.9%
Latin 12250996
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24915274
20.3%
2 15800587
12.9%
1 15029854
12.3%
/ 12250996
10.0%
12250996
10.0%
: 12250996
10.0%
3 5716494
 
4.7%
5 5362871
 
4.4%
4 5329705
 
4.4%
9 3443016
 
2.8%
Other values (3) 10159171
8.3%
Latin
ValueCountFrequency (%)
M 6125498
50.0%
P 3725204
30.4%
A 2400294
 
19.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134760956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24915274
18.5%
2 15800587
11.7%
1 15029854
11.2%
/ 12250996
9.1%
12250996
9.1%
: 12250996
9.1%
M 6125498
 
4.5%
3 5716494
 
4.2%
5 5362871
 
4.0%
4 5329705
 
4.0%
Other values (6) 19727685
14.6%

Response DtTm
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct5620807
Distinct (%)98.8%
Missing435276
Missing (%)7.1%
Memory size46.7 MiB
02/24/2017 12:04:50 PM
 
14
01/14/2018 05:04:46 AM
 
14
01/29/2023 02:31:59 AM
 
13
02/05/2023 02:45:28 AM
 
12
02/11/2017 08:39:56 AM
 
12
Other values (5620802)
5690157 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters125184884
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5553888 ?
Unique (%)97.6%

Sample

1st row05/01/2022 03:01:06 AM
2nd row01/19/2022 01:46:47 AM
3rd row05/03/2021 09:29:10 PM
4th row10/20/2021 10:11:55 PM
5th row04/30/2022 06:38:17 PM

Common Values

ValueCountFrequency (%)
02/24/2017 12:04:50 PM 14
 
< 0.1%
01/14/2018 05:04:46 AM 14
 
< 0.1%
01/29/2023 02:31:59 AM 13
 
< 0.1%
02/05/2023 02:45:28 AM 12
 
< 0.1%
02/11/2017 08:39:56 AM 12
 
< 0.1%
08/26/2014 12:45:04 AM 11
 
< 0.1%
04/07/2020 02:34:12 PM 10
 
< 0.1%
02/29/2020 08:59:29 PM 10
 
< 0.1%
10/06/2022 10:36:40 PM 10
 
< 0.1%
05/09/2014 08:55:50 AM 10
 
< 0.1%
Other values (5620797) 5690106
92.9%
(Missing) 435276
 
7.1%

Length

2023-02-21T23:28:19.133445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 3453938
 
20.2%
am 2236284
 
13.1%
09/02/2017 1677
 
< 0.1%
09/01/2017 1658
 
< 0.1%
10/24/2021 1532
 
< 0.1%
06/10/2019 1367
 
< 0.1%
12/31/2022 1221
 
< 0.1%
10/19/2022 1217
 
< 0.1%
12/17/2021 1187
 
< 0.1%
12/07/2019 1181
 
< 0.1%
Other values (51532) 11369404
66.6%

Most occurring characters

ValueCountFrequency (%)
0 23035014
18.4%
2 14733000
11.8%
1 14007098
11.2%
/ 11380444
9.1%
11380444
9.1%
: 11380444
9.1%
M 5690222
 
4.5%
3 5293825
 
4.2%
5 4983408
 
4.0%
4 4948112
 
4.0%
Other values (6) 18352873
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79663108
63.6%
Other Punctuation 22760888
 
18.2%
Space Separator 11380444
 
9.1%
Uppercase Letter 11380444
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23035014
28.9%
2 14733000
18.5%
1 14007098
17.6%
3 5293825
 
6.6%
5 4983408
 
6.3%
4 4948112
 
6.2%
9 3206773
 
4.0%
8 3200480
 
4.0%
7 3148853
 
4.0%
6 3106545
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 5690222
50.0%
P 3453938
30.3%
A 2236284
 
19.7%
Other Punctuation
ValueCountFrequency (%)
/ 11380444
50.0%
: 11380444
50.0%
Space Separator
ValueCountFrequency (%)
11380444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113804440
90.9%
Latin 11380444
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23035014
20.2%
2 14733000
12.9%
1 14007098
12.3%
/ 11380444
10.0%
11380444
10.0%
: 11380444
10.0%
3 5293825
 
4.7%
5 4983408
 
4.4%
4 4948112
 
4.3%
9 3206773
 
2.8%
Other values (3) 9455878
8.3%
Latin
ValueCountFrequency (%)
M 5690222
50.0%
P 3453938
30.3%
A 2236284
 
19.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125184884
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23035014
18.4%
2 14733000
11.8%
1 14007098
11.2%
/ 11380444
9.1%
11380444
9.1%
: 11380444
9.1%
M 5690222
 
4.5%
3 5293825
 
4.2%
5 4983408
 
4.0%
4 4948112
 
4.0%
Other values (6) 18352873
14.7%

On Scene DtTm
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct4717666
Distinct (%)99.0%
Missing1358394
Missing (%)22.2%
Memory size46.7 MiB
08/26/2014 12:45:04 AM
 
25
03/17/2002 12:47:48 AM
 
21
10/02/2006 02:30:16 PM
 
19
12/29/2012 12:05:18 PM
 
18
08/01/2000 04:08:36 PM
 
18
Other values (4717661)
4767003 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters104876288
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4674715 ?
Unique (%)98.1%

Sample

1st row05/01/2022 03:02:27 AM
2nd row01/19/2022 01:49:32 AM
3rd row05/03/2021 09:32:15 PM
4th row10/20/2021 05:53:45 PM
5th row04/30/2022 02:31:58 PM

Common Values

ValueCountFrequency (%)
08/26/2014 12:45:04 AM 25
 
< 0.1%
03/17/2002 12:47:48 AM 21
 
< 0.1%
10/02/2006 02:30:16 PM 19
 
< 0.1%
12/29/2012 12:05:18 PM 18
 
< 0.1%
08/01/2000 04:08:36 PM 18
 
< 0.1%
04/30/2001 09:55:13 AM 18
 
< 0.1%
05/03/2001 10:19:39 AM 17
 
< 0.1%
06/01/2001 07:02:56 AM 17
 
< 0.1%
10/17/2001 06:11:35 PM 16
 
< 0.1%
07/18/2001 02:13:52 AM 16
 
< 0.1%
Other values (4717656) 4766919
77.8%
(Missing) 1358394
 
22.2%

Length

2023-02-21T23:28:19.533078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 2898822
 
20.3%
am 1868282
 
13.1%
09/01/2017 1326
 
< 0.1%
09/02/2017 1323
 
< 0.1%
10/24/2021 1230
 
< 0.1%
06/10/2019 1123
 
< 0.1%
12/31/2022 1001
 
< 0.1%
01/01/2012 999
 
< 0.1%
12/07/2019 976
 
< 0.1%
01/01/2016 947
 
< 0.1%
Other values (51507) 9525283
66.6%

Most occurring characters

ValueCountFrequency (%)
0 19336172
18.4%
2 12302736
11.7%
1 11726733
11.2%
/ 9534208
9.1%
9534208
9.1%
: 9534208
9.1%
M 4767104
 
4.5%
3 4436898
 
4.2%
5 4178019
 
4.0%
4 4145098
 
4.0%
Other values (6) 15380904
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66739456
63.6%
Other Punctuation 19068416
 
18.2%
Space Separator 9534208
 
9.1%
Uppercase Letter 9534208
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19336172
29.0%
2 12302736
18.4%
1 11726733
17.6%
3 4436898
 
6.6%
5 4178019
 
6.3%
4 4145098
 
6.2%
9 2687917
 
4.0%
8 2684219
 
4.0%
7 2637728
 
4.0%
6 2603936
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 4767104
50.0%
P 2898822
30.4%
A 1868282
 
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 9534208
50.0%
: 9534208
50.0%
Space Separator
ValueCountFrequency (%)
9534208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95342080
90.9%
Latin 9534208
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19336172
20.3%
2 12302736
12.9%
1 11726733
12.3%
/ 9534208
10.0%
9534208
10.0%
: 9534208
10.0%
3 4436898
 
4.7%
5 4178019
 
4.4%
4 4145098
 
4.3%
9 2687917
 
2.8%
Other values (3) 7925883
8.3%
Latin
ValueCountFrequency (%)
M 4767104
50.0%
P 2898822
30.4%
A 1868282
 
19.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104876288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19336172
18.4%
2 12302736
11.7%
1 11726733
11.2%
/ 9534208
9.1%
9534208
9.1%
: 9534208
9.1%
M 4767104
 
4.5%
3 4436898
 
4.2%
5 4178019
 
4.0%
4 4145098
 
4.0%
Other values (6) 15380904
14.7%

Transport DtTm
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct1605017
Distinct (%)99.8%
Missing4518068
Missing (%)73.8%
Memory size46.7 MiB
08/16/2020 07:37:18 PM
 
6
11/17/2015 03:14:30 PM
 
4
07/14/2021 03:51:28 PM
 
4
05/21/2010 09:10:34 AM
 
4
08/12/2019 10:20:13 PM
 
3
Other values (1605012)
1607409 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters35363460
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1602683 ?
Unique (%)99.7%

Sample

1st row01/11/2022 02:04:39 PM
2nd row07/13/2021 02:51:27 AM
3rd row07/13/2021 02:51:42 AM
4th row07/13/2021 03:29:15 AM
5th row05/03/2021 03:04:39 AM

Common Values

ValueCountFrequency (%)
08/16/2020 07:37:18 PM 6
 
< 0.1%
11/17/2015 03:14:30 PM 4
 
< 0.1%
07/14/2021 03:51:28 PM 4
 
< 0.1%
05/21/2010 09:10:34 AM 4
 
< 0.1%
08/12/2019 10:20:13 PM 3
 
< 0.1%
10/14/2004 04:41:02 PM 3
 
< 0.1%
11/04/2020 05:32:51 PM 3
 
< 0.1%
05/26/2020 05:14:13 PM 3
 
< 0.1%
09/12/2017 02:23:05 AM 3
 
< 0.1%
05/21/2021 02:37:14 AM 3
 
< 0.1%
Other values (1605007) 1607394
 
26.2%
(Missing) 4518068
73.8%

Length

2023-02-21T23:28:19.743804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 965863
 
20.0%
am 641567
 
13.3%
09/02/2017 449
 
< 0.1%
09/01/2017 406
 
< 0.1%
06/10/2019 353
 
< 0.1%
09/03/2017 339
 
< 0.1%
01/01/2017 338
 
< 0.1%
01/01/2018 332
 
< 0.1%
01/01/2012 319
 
< 0.1%
06/11/2019 318
 
< 0.1%
Other values (51532) 3212006
66.6%

Most occurring characters

ValueCountFrequency (%)
0 6518486
18.4%
2 4146126
11.7%
1 3978582
11.3%
/ 3214860
9.1%
3214860
9.1%
: 3214860
9.1%
M 1607430
 
4.5%
3 1493602
 
4.2%
5 1407928
 
4.0%
4 1396126
 
3.9%
Other values (6) 5170600
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22504020
63.6%
Other Punctuation 6429720
 
18.2%
Space Separator 3214860
 
9.1%
Uppercase Letter 3214860
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6518486
29.0%
2 4146126
18.4%
1 3978582
17.7%
3 1493602
 
6.6%
5 1407928
 
6.3%
4 1396126
 
6.2%
9 905626
 
4.0%
8 901120
 
4.0%
7 884873
 
3.9%
6 871551
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 1607430
50.0%
P 965863
30.0%
A 641567
 
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 3214860
50.0%
: 3214860
50.0%
Space Separator
ValueCountFrequency (%)
3214860
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32148600
90.9%
Latin 3214860
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6518486
20.3%
2 4146126
12.9%
1 3978582
12.4%
/ 3214860
10.0%
3214860
10.0%
: 3214860
10.0%
3 1493602
 
4.6%
5 1407928
 
4.4%
4 1396126
 
4.3%
9 905626
 
2.8%
Other values (3) 2657544
8.3%
Latin
ValueCountFrequency (%)
M 1607430
50.0%
P 965863
30.0%
A 641567
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35363460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6518486
18.4%
2 4146126
11.7%
1 3978582
11.3%
/ 3214860
9.1%
3214860
9.1%
: 3214860
9.1%
M 1607430
 
4.5%
3 1493602
 
4.2%
5 1407928
 
4.0%
4 1396126
 
3.9%
Other values (6) 5170600
14.6%

Hospital DtTm
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct1468126
Distinct (%)99.8%
Missing4655157
Missing (%)76.0%
Memory size46.7 MiB
10/16/2016 04:02:09 AM
 
4
10/02/2006 05:02:06 PM
 
4
01/02/2011 03:09:24 PM
 
4
07/07/2007 06:03:05 PM
 
3
02/07/2017 10:00:26 PM
 
3
Other values (1468121)
1470323 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters32347502
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1465958 ?
Unique (%)99.7%

Sample

1st row01/11/2022 02:52:05 PM
2nd row07/13/2021 02:55:34 AM
3rd row07/13/2021 02:57:45 AM
4th row07/13/2021 03:37:07 AM
5th row05/03/2021 03:06:30 AM

Common Values

ValueCountFrequency (%)
10/16/2016 04:02:09 AM 4
 
< 0.1%
10/02/2006 05:02:06 PM 4
 
< 0.1%
01/02/2011 03:09:24 PM 4
 
< 0.1%
07/07/2007 06:03:05 PM 3
 
< 0.1%
02/07/2017 10:00:26 PM 3
 
< 0.1%
02/15/2014 02:55:46 PM 3
 
< 0.1%
10/25/2009 10:19:32 PM 3
 
< 0.1%
03/12/2005 11:21:17 AM 3
 
< 0.1%
05/12/2018 09:48:05 PM 3
 
< 0.1%
11/11/2003 01:50:53 PM 3
 
< 0.1%
Other values (1468116) 1470308
 
24.0%
(Missing) 4655157
76.0%

Length

2023-02-21T23:28:19.948834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 893670
 
20.3%
am 576671
 
13.1%
09/02/2017 436
 
< 0.1%
09/01/2017 382
 
< 0.1%
09/03/2017 342
 
< 0.1%
06/10/2019 339
 
< 0.1%
01/01/2017 338
 
< 0.1%
01/01/2018 330
 
< 0.1%
06/11/2019 317
 
< 0.1%
01/01/2012 309
 
< 0.1%
Other values (51532) 2937889
66.6%

Most occurring characters

ValueCountFrequency (%)
0 5901952
18.2%
2 3805726
11.8%
1 3675441
11.4%
/ 2940682
9.1%
2940682
9.1%
: 2940682
9.1%
M 1470341
 
4.5%
3 1366677
 
4.2%
5 1281037
 
4.0%
4 1262906
 
3.9%
Other values (6) 4761376
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20584774
63.6%
Other Punctuation 5881364
 
18.2%
Space Separator 2940682
 
9.1%
Uppercase Letter 2940682
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5901952
28.7%
2 3805726
18.5%
1 3675441
17.9%
3 1366677
 
6.6%
5 1281037
 
6.2%
4 1262906
 
6.1%
8 840094
 
4.1%
9 834914
 
4.1%
7 817770
 
4.0%
6 798257
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 1470341
50.0%
P 893670
30.4%
A 576671
 
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 2940682
50.0%
: 2940682
50.0%
Space Separator
ValueCountFrequency (%)
2940682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29406820
90.9%
Latin 2940682
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5901952
20.1%
2 3805726
12.9%
1 3675441
12.5%
/ 2940682
10.0%
2940682
10.0%
: 2940682
10.0%
3 1366677
 
4.6%
5 1281037
 
4.4%
4 1262906
 
4.3%
8 840094
 
2.9%
Other values (3) 2450941
8.3%
Latin
ValueCountFrequency (%)
M 1470341
50.0%
P 893670
30.4%
A 576671
 
19.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32347502
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5901952
18.2%
2 3805726
11.8%
1 3675441
11.4%
/ 2940682
9.1%
2940682
9.1%
: 2940682
9.1%
M 1470341
 
4.5%
3 1366677
 
4.2%
5 1281037
 
4.0%
4 1262906
 
3.9%
Other values (6) 4761376
14.7%
Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
Other
2540692 
Code 2 Transport
1818641 
Fire
849461 
Patient Declined Transport
 
235693
No Merit
 
206129
Other values (10)
474882 

Length

Max length26
Median length23
Mean length9.8095663
Min length3

Characters and Unicode

Total characters60088479
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFire
2nd rowFire
3rd rowFire
4th rowFire
5th rowFire

Common Values

ValueCountFrequency (%)
Other 2540692
41.5%
Code 2 Transport 1818641
29.7%
Fire 849461
 
13.9%
Patient Declined Transport 235693
 
3.8%
No Merit 206129
 
3.4%
Code 3 Transport 160951
 
2.6%
Cancelled 71895
 
1.2%
Against Medical Advice 71427
 
1.2%
Unable to Locate 69320
 
1.1%
Medical Examiner 48572
 
0.8%
Other values (5) 52717
 
0.9%

Length

2023-02-21T23:28:20.032881image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
other 2540692
22.8%
transport 2215285
19.9%
code 1979592
17.8%
2 1818641
16.3%
fire 849461
 
7.6%
patient 235693
 
2.1%
declined 235693
 
2.1%
no 206129
 
1.9%
merit 206129
 
1.9%
3 160951
 
1.4%
Other values (16) 682147
 
6.1%

Most occurring characters

ValueCountFrequency (%)
r 8113198
13.5%
e 6826078
11.4%
t 5646121
 
9.4%
5004915
 
8.3%
o 4577420
 
7.6%
n 2986411
 
5.0%
a 2922584
 
4.9%
O 2540692
 
4.2%
h 2540692
 
4.2%
d 2478982
 
4.1%
Other values (30) 16451386
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43945929
73.1%
Uppercase Letter 9157667
 
15.2%
Space Separator 5004915
 
8.3%
Decimal Number 1979592
 
3.3%
Dash Punctuation 376
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 8113198
18.5%
e 6826078
15.5%
t 5646121
12.8%
o 4577420
10.4%
n 2986411
 
6.8%
a 2922584
 
6.7%
h 2540692
 
5.8%
d 2478982
 
5.6%
s 2287088
 
5.2%
p 2216719
 
5.0%
Other values (10) 3350636
7.6%
Uppercase Letter
ValueCountFrequency (%)
O 2540692
27.7%
T 2215285
24.2%
C 2052494
22.4%
F 880474
 
9.6%
M 326504
 
3.6%
D 268140
 
2.9%
P 267713
 
2.9%
N 206129
 
2.3%
A 161741
 
1.8%
L 69320
 
0.8%
Other values (6) 169175
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 1818641
91.9%
3 160951
 
8.1%
Space Separator
ValueCountFrequency (%)
5004915
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 376
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 53103596
88.4%
Common 6984883
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 8113198
15.3%
e 6826078
12.9%
t 5646121
10.6%
o 4577420
 
8.6%
n 2986411
 
5.6%
a 2922584
 
5.5%
O 2540692
 
4.8%
h 2540692
 
4.8%
d 2478982
 
4.7%
s 2287088
 
4.3%
Other values (26) 12184330
22.9%
Common
ValueCountFrequency (%)
5004915
71.7%
2 1818641
 
26.0%
3 160951
 
2.3%
- 376
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60088479
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 8113198
13.5%
e 6826078
11.4%
t 5646121
 
9.4%
5004915
 
8.3%
o 4577420
 
7.6%
n 2986411
 
5.0%
a 2922584
 
4.9%
O 2540692
 
4.2%
h 2540692
 
4.2%
d 2478982
 
4.1%
Other values (30) 16451386
27.4%

Available DtTm
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct5704138
Distinct (%)94.3%
Missing77143
Missing (%)1.3%
Memory size46.7 MiB
09/04/2014 04:54:29 PM
 
42
11/08/2012 07:18:14 PM
 
21
10/20/2020 02:58:03 PM
 
21
04/03/2008 08:07:22 PM
 
17
11/02/2001 10:17:45 AM
 
17
Other values (5704133)
6048237 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters133063810
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5469065 ?
Unique (%)90.4%

Sample

1st row05/01/2022 03:05:00 AM
2nd row01/19/2022 02:35:26 AM
3rd row05/03/2021 09:38:09 PM
4th row10/20/2021 10:25:52 PM
5th row04/30/2022 06:40:08 PM

Common Values

ValueCountFrequency (%)
09/04/2014 04:54:29 PM 42
 
< 0.1%
11/08/2012 07:18:14 PM 21
 
< 0.1%
10/20/2020 02:58:03 PM 21
 
< 0.1%
04/03/2008 08:07:22 PM 17
 
< 0.1%
11/02/2001 10:17:45 AM 17
 
< 0.1%
03/12/2014 07:22:43 AM 16
 
< 0.1%
09/05/2022 04:32:23 PM 16
 
< 0.1%
07/11/2013 05:12:21 PM 15
 
< 0.1%
05/28/2015 08:40:37 PM 14
 
< 0.1%
06/26/2012 08:02:49 PM 14
 
< 0.1%
Other values (5704128) 6048162
98.7%
(Missing) 77143
 
1.3%

Length

2023-02-21T23:28:20.561760image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm 3742129
 
20.6%
am 2306226
 
12.7%
09/01/2017 1733
 
< 0.1%
09/02/2017 1722
 
< 0.1%
10/24/2021 1583
 
< 0.1%
06/10/2019 1391
 
< 0.1%
01/01/2012 1338
 
< 0.1%
10/19/2022 1269
 
< 0.1%
06/14/2000 1257
 
< 0.1%
12/31/2022 1241
 
< 0.1%
Other values (51532) 12085176
66.6%

Most occurring characters

ValueCountFrequency (%)
0 24557841
18.5%
2 15644130
11.8%
1 14868909
11.2%
/ 12096710
9.1%
12096710
9.1%
: 12096710
9.1%
M 6048355
 
4.5%
3 5659691
 
4.3%
5 5292418
 
4.0%
4 5263337
 
4.0%
Other values (6) 19438999
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84676970
63.6%
Other Punctuation 24193420
 
18.2%
Space Separator 12096710
 
9.1%
Uppercase Letter 12096710
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24557841
29.0%
2 15644130
18.5%
1 14868909
17.6%
3 5659691
 
6.7%
5 5292418
 
6.3%
4 5263337
 
6.2%
9 3394553
 
4.0%
8 3378680
 
4.0%
7 3327111
 
3.9%
6 3290300
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
M 6048355
50.0%
P 3742129
30.9%
A 2306226
 
19.1%
Other Punctuation
ValueCountFrequency (%)
/ 12096710
50.0%
: 12096710
50.0%
Space Separator
ValueCountFrequency (%)
12096710
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120967100
90.9%
Latin 12096710
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24557841
20.3%
2 15644130
12.9%
1 14868909
12.3%
/ 12096710
10.0%
12096710
10.0%
: 12096710
10.0%
3 5659691
 
4.7%
5 5292418
 
4.4%
4 5263337
 
4.4%
9 3394553
 
2.8%
Other values (3) 9996091
8.3%
Latin
ValueCountFrequency (%)
M 6048355
50.0%
P 3742129
30.9%
A 2306226
 
19.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133063810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24557841
18.5%
2 15644130
11.8%
1 14868909
11.2%
/ 12096710
9.1%
12096710
9.1%
: 12096710
9.1%
M 6048355
 
4.5%
3 5659691
 
4.3%
5 5292418
 
4.0%
4 5263337
 
4.0%
Other values (6) 19438999
14.6%

Address
Categorical

Distinct34050
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
0 Block of 6TH ST
 
36481
800 Block of MARKET ST
 
31051
200 Block of EDDY ST
 
25951
1100 Block of MARKET ST
 
25916
300 Block of EDDY ST
 
24806
Other values (34045)
5981293 

Length

Max length44
Median length40
Mean length22.03663
Min length3

Characters and Unicode

Total characters134985336
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2528 ?
Unique (%)< 0.1%

Sample

1st rowGOUGH ST/GROVE ST
2nd row100 Block of MISSISSIPPI ST
3rd row0 Block of HOFF ST
4th row200 Block of JONES ST
5th row1400 Block of FILBERT ST

Common Values

ValueCountFrequency (%)
0 Block of 6TH ST 36481
 
0.6%
800 Block of MARKET ST 31051
 
0.5%
200 Block of EDDY ST 25951
 
0.4%
1100 Block of MARKET ST 25916
 
0.4%
300 Block of EDDY ST 24806
 
0.4%
100 Block of 6TH ST 24012
 
0.4%
300 Block of ELLIS ST 23091
 
0.4%
500 Block of 5TH ST 22228
 
0.4%
1000 Block of POLK ST 21380
 
0.3%
400 Block of ELLIS ST 20443
 
0.3%
Other values (34040) 5870139
95.8%

Length

2023-02-21T23:28:20.660354image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of 4740450
16.6%
block 4734146
16.6%
st 4299792
 
15.1%
ave 909635
 
3.2%
0 570750
 
2.0%
100 414414
 
1.5%
200 340972
 
1.2%
300 327274
 
1.1%
400 283425
 
1.0%
av 281382
 
1.0%
Other values (8780) 11651907
40.8%

Most occurring characters

ValueCountFrequency (%)
22428670
16.6%
o 9468293
 
7.0%
0 9288560
 
6.9%
T 8847328
 
6.6%
S 8307192
 
6.2%
A 5955038
 
4.4%
B 5783015
 
4.3%
E 5093008
 
3.8%
l 4734146
 
3.5%
c 4734146
 
3.5%
Other values (49) 50345940
37.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 65782513
48.7%
Lowercase Letter 28404885
21.0%
Space Separator 22428670
 
16.6%
Decimal Number 16949558
 
12.6%
Other Punctuation 1405625
 
1.0%
Dash Punctuation 14060
 
< 0.1%
Math Symbol 25
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 8847328
13.4%
S 8307192
12.6%
A 5955038
 
9.1%
B 5783015
 
8.8%
E 5093008
 
7.7%
R 3693622
 
5.6%
O 3556763
 
5.4%
N 3469193
 
5.3%
L 3094910
 
4.7%
I 2517401
 
3.8%
Other values (16) 15465043
23.5%
Lowercase Letter
ValueCountFrequency (%)
o 9468293
33.3%
l 4734146
16.7%
c 4734146
16.7%
k 4734146
16.7%
f 4734146
16.7%
n 2
 
< 0.1%
e 2
 
< 0.1%
h 1
 
< 0.1%
t 1
 
< 0.1%
v 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 9288560
54.8%
1 2155305
 
12.7%
2 1365974
 
8.1%
3 949673
 
5.6%
4 747705
 
4.4%
5 595329
 
3.5%
6 585244
 
3.5%
7 459375
 
2.7%
8 441566
 
2.6%
9 360827
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 1342194
95.5%
: 53294
 
3.8%
, 9438
 
0.7%
# 472
 
< 0.1%
* 98
 
< 0.1%
. 61
 
< 0.1%
' 37
 
< 0.1%
& 31
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
< 23
92.0%
~ 2
 
8.0%
Space Separator
ValueCountFrequency (%)
22428670
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 94187398
69.8%
Common 40797938
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 9468293
 
10.1%
T 8847328
 
9.4%
S 8307192
 
8.8%
A 5955038
 
6.3%
B 5783015
 
6.1%
E 5093008
 
5.4%
l 4734146
 
5.0%
c 4734146
 
5.0%
k 4734146
 
5.0%
f 4734146
 
5.0%
Other values (27) 31796940
33.8%
Common
ValueCountFrequency (%)
22428670
55.0%
0 9288560
22.8%
1 2155305
 
5.3%
2 1365974
 
3.3%
/ 1342194
 
3.3%
3 949673
 
2.3%
4 747705
 
1.8%
5 595329
 
1.5%
6 585244
 
1.4%
7 459375
 
1.1%
Other values (12) 879909
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134985336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22428670
16.6%
o 9468293
 
7.0%
0 9288560
 
6.9%
T 8847328
 
6.6%
S 8307192
 
6.2%
A 5955038
 
4.4%
B 5783015
 
4.3%
E 5093008
 
3.8%
l 4734146
 
3.5%
c 4734146
 
3.5%
Other values (49) 50345940
37.3%

City
Categorical

Distinct27
Distinct (%)< 0.1%
Missing9090
Missing (%)0.1%
Memory size46.7 MiB
SF
3351970 
San Francisco
2648980 
SAN FRANCISCO
 
42631
Presidio
 
14252
TI
 
13783
Other values (22)
 
44792

Length

Max length15
Median length2
Mean length6.8905027
Min length2

Characters and Unicode

Total characters42145126
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSan Francisco
2nd rowSan Francisco
3rd rowSan Francisco
4th rowSan Francisco
5th rowSan Francisco

Common Values

ValueCountFrequency (%)
SF 3351970
54.7%
San Francisco 2648980
43.2%
SAN FRANCISCO 42631
 
0.7%
Presidio 14252
 
0.2%
TI 13783
 
0.2%
Treasure Isla 12941
 
0.2%
PR 9949
 
0.2%
SFO 9399
 
0.2%
Yerba Buena 2276
 
< 0.1%
Hunters Point 1914
 
< 0.1%
Other values (17) 8313
 
0.1%
(Missing) 9090
 
0.1%

Length

2023-02-21T23:28:20.738806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sf 3351970
38.0%
francisco 2691611
30.5%
san 2691611
30.5%
presidio 14469
 
0.2%
ti 13783
 
0.2%
treasure 13378
 
0.2%
isla 12941
 
0.1%
pr 9949
 
0.1%
sfo 9399
 
0.1%
yerba 2288
 
< 0.1%
Other values (17) 16496
 
0.2%

Most occurring characters

ValueCountFrequency (%)
S 6096191
14.5%
F 6056317
14.4%
a 5331293
12.6%
n 5306206
12.6%
c 5297960
12.6%
2711487
6.4%
r 2695723
6.4%
s 2693447
6.4%
i 2679983
6.4%
o 2668666
6.3%
Other values (24) 607853
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26775581
63.5%
Uppercase Letter 12658058
30.0%
Space Separator 2711487
 
6.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 6096191
48.2%
F 6056317
47.8%
C 86909
 
0.7%
A 85926
 
0.7%
N 85820
 
0.7%
I 70289
 
0.6%
R 53160
 
0.4%
O 52550
 
0.4%
T 27208
 
0.2%
P 27021
 
0.2%
Other values (9) 16667
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
a 5331293
19.9%
n 5306206
19.8%
c 5297960
19.8%
r 2695723
10.1%
s 2693447
10.1%
i 2679983
10.0%
o 2668666
10.0%
e 47259
 
0.2%
u 17408
 
0.1%
d 14529
 
0.1%
Other values (4) 23107
 
0.1%
Space Separator
ValueCountFrequency (%)
2711487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39433639
93.6%
Common 2711487
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 6096191
15.5%
F 6056317
15.4%
a 5331293
13.5%
n 5306206
13.5%
c 5297960
13.4%
r 2695723
6.8%
s 2693447
6.8%
i 2679983
6.8%
o 2668666
6.8%
C 86909
 
0.2%
Other values (23) 520944
 
1.3%
Common
ValueCountFrequency (%)
2711487
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42145126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 6096191
14.5%
F 6056317
14.4%
a 5331293
12.6%
n 5306206
12.6%
c 5297960
12.6%
2711487
6.4%
r 2695723
6.4%
s 2693447
6.4%
i 2679983
6.4%
o 2668666
6.3%
Other values (24) 607853
 
1.4%

Zipcode of Incident
Real number (ℝ)

Distinct27
Distinct (%)< 0.1%
Missing14859
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean94113.502
Minimum94102
Maximum94158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 MiB
2023-02-21T23:28:20.833002image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum94102
5-th percentile94102
Q194103
median94110
Q394121
95-th percentile94133
Maximum94158
Range56
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.278535
Coefficient of variation (CV)0.00010921424
Kurtosis0.86624909
Mean94113.502
Median Absolute Deviation (MAD)7
Skewness0.96947054
Sum5.7509364 × 1011
Variance105.64828
MonotonicityNot monotonic
2023-02-21T23:28:20.896186image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
94102 780776
 
12.7%
94103 749986
 
12.2%
94109 524048
 
8.6%
94110 510262
 
8.3%
94124 320309
 
5.2%
94112 284677
 
4.6%
94115 270193
 
4.4%
94107 240333
 
3.9%
94122 215560
 
3.5%
94133 212240
 
3.5%
Other values (17) 2002255
32.7%
ValueCountFrequency (%)
94102 780776
12.7%
94103 749986
12.2%
94104 43373
 
0.7%
94105 145789
 
2.4%
94107 240333
 
3.9%
94108 139132
 
2.3%
94109 524048
8.6%
94110 510262
8.3%
94111 101408
 
1.7%
94112 284677
 
4.6%
ValueCountFrequency (%)
94158 35159
 
0.6%
94134 167206
2.7%
94133 212240
3.5%
94132 147045
2.4%
94131 112491
 
1.8%
94130 41340
 
0.7%
94129 22603
 
0.4%
94127 62384
 
1.0%
94124 320309
5.2%
94123 130057
2.1%

Battalion
Categorical

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
B02
1068414 
B03
1058705 
B01
662648 
B04
605966 
B10
520087 
Other values (10)
2209678 

Length

Max length4
Median length3
Mean length2.9999998
Min length2

Characters and Unicode

Total characters18376493
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowB02
2nd rowB03
3rd rowB02
4th rowB03
5th rowB04

Common Values

ValueCountFrequency (%)
B02 1068414
17.4%
B03 1058705
17.3%
B01 662648
10.8%
B04 605966
9.9%
B10 520087
8.5%
B08 488085
8.0%
B09 473082
7.7%
B06 447921
7.3%
B05 441360
7.2%
B07 320913
 
5.2%
Other values (5) 38317
 
0.6%

Length

2023-02-21T23:28:21.011005image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
b02 1068414
17.4%
b03 1058705
17.3%
b01 662648
10.8%
b04 605966
9.9%
b10 520087
8.5%
b08 488085
8.0%
b09 473082
7.7%
b06 447921
7.3%
b05 441360
7.2%
b07 320913
 
5.2%
Other values (5) 38317
 
0.6%

Most occurring characters

ValueCountFrequency (%)
B 6125496
33.3%
0 6087183
33.1%
1 1182737
 
6.4%
2 1068415
 
5.8%
3 1058707
 
5.8%
4 605966
 
3.3%
9 549704
 
3.0%
8 488085
 
2.7%
6 447921
 
2.4%
5 441360
 
2.4%
Other values (4) 320919
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12250991
66.7%
Uppercase Letter 6125502
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6087183
49.7%
1 1182737
 
9.7%
2 1068415
 
8.7%
3 1058707
 
8.6%
4 605966
 
4.9%
9 549704
 
4.5%
8 488085
 
4.0%
6 447921
 
3.7%
5 441360
 
3.6%
7 320913
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
B 6125496
> 99.9%
A 2
 
< 0.1%
M 2
 
< 0.1%
E 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 12250991
66.7%
Latin 6125502
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6087183
49.7%
1 1182737
 
9.7%
2 1068415
 
8.7%
3 1058707
 
8.6%
4 605966
 
4.9%
9 549704
 
4.5%
8 488085
 
4.0%
6 447921
 
3.7%
5 441360
 
3.6%
7 320913
 
2.6%
Latin
ValueCountFrequency (%)
B 6125496
> 99.9%
A 2
 
< 0.1%
M 2
 
< 0.1%
E 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18376493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 6125496
33.3%
0 6087183
33.1%
1 1182737
 
6.4%
2 1068415
 
5.8%
3 1058707
 
5.8%
4 605966
 
3.3%
9 549704
 
3.0%
8 488085
 
2.7%
6 447921
 
2.4%
5 441360
 
2.4%
Other values (4) 320919
 
1.7%

Station Area
Unsupported

REJECTED  UNSUPPORTED 

Missing2405
Missing (%)< 0.1%
Memory size46.7 MiB

Box
Unsupported

REJECTED  UNSUPPORTED 

Missing473
Missing (%)< 0.1%
Memory size46.7 MiB

Original Priority
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)< 0.1%
Missing25538
Missing (%)0.4%
Memory size46.7 MiB
3
4428500 
2
986720 
E
 
216213
1
 
189657
A
 
156652
Other values (4)
 
122218

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6099960
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd rowA
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4428500
72.3%
2 986720
 
16.1%
E 216213
 
3.5%
1 189657
 
3.1%
A 156652
 
2.6%
B 73964
 
1.2%
C 42633
 
0.7%
I 5577
 
0.1%
T 44
 
< 0.1%
(Missing) 25538
 
0.4%

Length

2023-02-21T23:28:21.086059image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:21.180856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4428500
72.6%
2 986720
 
16.2%
e 216213
 
3.5%
1 189657
 
3.1%
a 156652
 
2.6%
b 73964
 
1.2%
c 42633
 
0.7%
i 5577
 
0.1%
t 44
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
3 4428500
72.6%
2 986720
 
16.2%
E 216213
 
3.5%
1 189657
 
3.1%
A 156652
 
2.6%
B 73964
 
1.2%
C 42633
 
0.7%
I 5577
 
0.1%
T 44
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5604877
91.9%
Uppercase Letter 495083
 
8.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 216213
43.7%
A 156652
31.6%
B 73964
 
14.9%
C 42633
 
8.6%
I 5577
 
1.1%
T 44
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 4428500
79.0%
2 986720
 
17.6%
1 189657
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5604877
91.9%
Latin 495083
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 216213
43.7%
A 156652
31.6%
B 73964
 
14.9%
C 42633
 
8.6%
I 5577
 
1.1%
T 44
 
< 0.1%
Common
ValueCountFrequency (%)
3 4428500
79.0%
2 986720
 
17.6%
1 189657
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6099960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 4428500
72.6%
2 986720
 
16.2%
E 216213
 
3.5%
1 189657
 
3.1%
A 156652
 
2.6%
B 73964
 
1.2%
C 42633
 
0.7%
I 5577
 
0.1%
T 44
 
< 0.1%

Priority
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size46.7 MiB
3
4507028 
2
1153076 
E
 
257730
1
 
201582
A
 
3908
Other values (4)
 
2171

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6125495
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4507028
73.6%
2 1153076
 
18.8%
E 257730
 
4.2%
1 201582
 
3.3%
A 3908
 
0.1%
B 1685
 
< 0.1%
I 308
 
< 0.1%
C 173
 
< 0.1%
T 5
 
< 0.1%
(Missing) 3
 
< 0.1%

Length

2023-02-21T23:28:21.274416image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:21.352631image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4507028
73.6%
2 1153076
 
18.8%
e 257730
 
4.2%
1 201582
 
3.3%
a 3908
 
0.1%
b 1685
 
< 0.1%
i 308
 
< 0.1%
c 173
 
< 0.1%
t 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
3 4507028
73.6%
2 1153076
 
18.8%
E 257730
 
4.2%
1 201582
 
3.3%
A 3908
 
0.1%
B 1685
 
< 0.1%
I 308
 
< 0.1%
C 173
 
< 0.1%
T 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5861686
95.7%
Uppercase Letter 263809
 
4.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 257730
97.7%
A 3908
 
1.5%
B 1685
 
0.6%
I 308
 
0.1%
C 173
 
0.1%
T 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 4507028
76.9%
2 1153076
 
19.7%
1 201582
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5861686
95.7%
Latin 263809
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 257730
97.7%
A 3908
 
1.5%
B 1685
 
0.6%
I 308
 
0.1%
C 173
 
0.1%
T 5
 
< 0.1%
Common
ValueCountFrequency (%)
3 4507028
76.9%
2 1153076
 
19.7%
1 201582
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6125495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 4507028
73.6%
2 1153076
 
18.8%
E 257730
 
4.2%
1 201582
 
3.3%
A 3908
 
0.1%
B 1685
 
< 0.1%
I 308
 
< 0.1%
C 173
 
< 0.1%
T 5
 
< 0.1%

Final Priority
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
3
4765247 
2
1360251 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6125498
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

Length

2023-02-21T23:28:21.431221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:21.526712image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

Most occurring characters

ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6125498
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

Most occurring scripts

ValueCountFrequency (%)
Common 6125498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6125498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 4765247
77.8%
2 1360251
 
22.2%

ALS Unit
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 MiB
True
3814098 
False
2311400 
ValueCountFrequency (%)
True 3814098
62.3%
False 2311400
37.7%
2023-02-21T23:28:21.606674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Call Type Group
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing2818694
Missing (%)46.0%
Memory size46.7 MiB
Potentially Life-Threatening
1591493 
Non Life-threatening
799757 
Alarm
776902 
Fire
 
138652

Length

Max length28
Median length20
Mean length19.655251
Min length4

Characters and Unicode

Total characters64996062
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFire
2nd rowAlarm
3rd rowAlarm
4th rowAlarm
5th rowAlarm

Common Values

ValueCountFrequency (%)
Potentially Life-Threatening 1591493
26.0%
Non Life-threatening 799757
 
13.1%
Alarm 776902
 
12.7%
Fire 138652
 
2.3%
(Missing) 2818694
46.0%

Length

2023-02-21T23:28:21.684543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:21.764666image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
life-threatening 2391250
42.0%
potentially 1591493
27.9%
non 799757
 
14.0%
alarm 776902
 
13.6%
fire 138652
 
2.4%

Most occurring characters

ValueCountFrequency (%)
e 8903895
13.7%
n 7173750
11.0%
i 6512645
 
10.0%
t 6373993
 
9.8%
a 4759645
 
7.3%
l 3959888
 
6.1%
r 3306804
 
5.1%
L 2391250
 
3.7%
h 2391250
 
3.7%
g 2391250
 
3.7%
Other values (11) 16831692
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52924015
81.4%
Uppercase Letter 7289547
 
11.2%
Space Separator 2391250
 
3.7%
Dash Punctuation 2391250
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8903895
16.8%
n 7173750
13.6%
i 6512645
12.3%
t 6373993
12.0%
a 4759645
9.0%
l 3959888
7.5%
r 3306804
 
6.2%
h 2391250
 
4.5%
g 2391250
 
4.5%
o 2391250
 
4.5%
Other values (3) 4759645
9.0%
Uppercase Letter
ValueCountFrequency (%)
L 2391250
32.8%
P 1591493
21.8%
T 1591493
21.8%
N 799757
 
11.0%
A 776902
 
10.7%
F 138652
 
1.9%
Space Separator
ValueCountFrequency (%)
2391250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2391250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60213562
92.6%
Common 4782500
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8903895
14.8%
n 7173750
11.9%
i 6512645
10.8%
t 6373993
10.6%
a 4759645
 
7.9%
l 3959888
 
6.6%
r 3306804
 
5.5%
L 2391250
 
4.0%
h 2391250
 
4.0%
g 2391250
 
4.0%
Other values (9) 12049192
20.0%
Common
ValueCountFrequency (%)
2391250
50.0%
- 2391250
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64996062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8903895
13.7%
n 7173750
11.0%
i 6512645
 
10.0%
t 6373993
 
9.8%
a 4759645
 
7.3%
l 3959888
 
6.1%
r 3306804
 
5.1%
L 2391250
 
3.7%
h 2391250
 
3.7%
g 2391250
 
3.7%
Other values (11) 16831692
25.9%

Number of Alarms
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
1
6104895 
2
 
13636
3
 
4768
4
 
1623
5
 
576

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6125498
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Length

2023-02-21T23:28:21.840625image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:21.935053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6125498
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6125498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6125498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6104895
99.7%
2 13636
 
0.2%
3 4768
 
0.1%
4 1623
 
< 0.1%
5 576
 
< 0.1%

Unit Type
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
ENGINE
2276351 
MEDIC
1894247 
TRUCK
647262 
CHIEF
454768 
PRIVATE
425454 
Other values (5)
427416 

Length

Max length14
Median length13
Mean length5.9826148
Min length5

Characters and Unicode

Total characters36646495
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENGINE
2nd rowENGINE
3rd rowTRUCK
4th rowCHIEF
5th rowENGINE

Common Values

ValueCountFrequency (%)
ENGINE 2276351
37.2%
MEDIC 1894247
30.9%
TRUCK 647262
 
10.6%
CHIEF 454768
 
7.4%
PRIVATE 425454
 
6.9%
RESCUE CAPTAIN 210469
 
3.4%
RESCUE SQUAD 105147
 
1.7%
SUPPORT 86005
 
1.4%
AIRPORT 19479
 
0.3%
INVESTIGATION 6316
 
0.1%

Length

2023-02-21T23:28:22.019897image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-21T23:28:22.233780image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
engine 2276351
35.3%
medic 1894247
29.4%
truck 647262
 
10.0%
chief 454768
 
7.1%
private 425454
 
6.6%
rescue 315616
 
4.9%
captain 210469
 
3.3%
squad 105147
 
1.6%
support 86005
 
1.3%
airport 19479
 
0.3%

Most occurring characters

ValueCountFrequency (%)
E 7964719
21.7%
I 5299716
14.5%
N 4775803
13.0%
C 3522362
9.6%
G 2282667
 
6.2%
D 1999394
 
5.5%
M 1894247
 
5.2%
R 1513295
 
4.1%
T 1401301
 
3.8%
U 1154030
 
3.1%
Other values (10) 4838961
13.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 36330879
99.1%
Space Separator 315616
 
0.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 7964719
21.9%
I 5299716
14.6%
N 4775803
13.1%
C 3522362
9.7%
G 2282667
 
6.3%
D 1999394
 
5.5%
M 1894247
 
5.2%
R 1513295
 
4.2%
T 1401301
 
3.9%
U 1154030
 
3.2%
Other values (9) 4523345
12.5%
Space Separator
ValueCountFrequency (%)
315616
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36330879
99.1%
Common 315616
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 7964719
21.9%
I 5299716
14.6%
N 4775803
13.1%
C 3522362
9.7%
G 2282667
 
6.3%
D 1999394
 
5.5%
M 1894247
 
5.2%
R 1513295
 
4.2%
T 1401301
 
3.9%
U 1154030
 
3.2%
Other values (9) 4523345
12.5%
Common
ValueCountFrequency (%)
315616
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36646495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 7964719
21.7%
I 5299716
14.5%
N 4775803
13.0%
C 3522362
9.6%
G 2282667
 
6.2%
D 1999394
 
5.5%
M 1894247
 
5.2%
R 1513295
 
4.1%
T 1401301
 
3.8%
U 1154030
 
3.1%
Other values (10) 4838961
13.2%
Distinct104
Distinct (%)< 0.1%
Missing72
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.1474441
Minimum1
Maximum104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 MiB
2023-02-21T23:28:22.361791image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile6
Maximum104
Range103
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1361633
Coefficient of variation (CV)0.99474687
Kurtosis117.66664
Mean2.1474441
Median Absolute Deviation (MAD)1
Skewness7.015522
Sum13154010
Variance4.5631937
MonotonicityNot monotonic
2023-02-21T23:28:22.456691image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2816475
46.0%
2 1923063
31.4%
3 784688
 
12.8%
4 194571
 
3.2%
5 90144
 
1.5%
6 64689
 
1.1%
7 53692
 
0.9%
8 48201
 
0.8%
9 45247
 
0.7%
10 42879
 
0.7%
Other values (94) 61777
 
1.0%
ValueCountFrequency (%)
1 2816475
46.0%
2 1923063
31.4%
3 784688
 
12.8%
4 194571
 
3.2%
5 90144
 
1.5%
6 64689
 
1.1%
7 53692
 
0.9%
8 48201
 
0.8%
9 45247
 
0.7%
10 42879
 
0.7%
ValueCountFrequency (%)
104 1
< 0.1%
103 1
< 0.1%
102 1
< 0.1%
101 1
< 0.1%
100 1
< 0.1%
99 1
< 0.1%
98 2
< 0.1%
97 2
< 0.1%
96 2
< 0.1%
95 2
< 0.1%
Distinct21
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
2
1187648 
3
917484 
1
668919 
4
554376 
10
494750 
Other values (16)
2302321 

Length

Max length4
Median length1
Mean length1.1360859
Min length1

Characters and Unicode

Total characters6959092
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row2
4th row3
5th row4

Common Values

ValueCountFrequency (%)
2 1187648
19.4%
3 917484
15.0%
1 668919
10.9%
4 554376
9.1%
10 494750
8.1%
9 474008
 
7.7%
6 465569
 
7.6%
8 437232
 
7.1%
5 422527
 
6.9%
7 369817
 
6.0%
Other values (11) 133168
 
2.2%

Length

2023-02-21T23:28:22.560592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1187648
19.4%
3 917484
15.0%
1 668919
10.9%
4 554376
9.1%
10 494750
8.1%
9 474008
 
7.7%
6 465569
 
7.6%
8 437232
 
7.1%
5 422527
 
6.9%
7 369817
 
6.0%
Other values (11) 133168
 
2.2%

Most occurring characters

ValueCountFrequency (%)
2 1196111
17.2%
1 1178521
16.9%
3 925378
13.3%
0 576376
8.3%
4 558149
8.0%
9 482269
6.9%
6 473328
 
6.8%
8 445869
 
6.4%
5 426891
 
6.1%
7 376957
 
5.4%
Other values (5) 319243
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6639849
95.4%
Lowercase Letter 186075
 
2.7%
Other Punctuation 71143
 
1.0%
Uppercase Letter 62025
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1196111
18.0%
1 1178521
17.7%
3 925378
13.9%
0 576376
8.7%
4 558149
8.4%
9 482269
7.3%
6 473328
 
7.1%
8 445869
 
6.7%
5 426891
 
6.4%
7 376957
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
o 62025
33.3%
n 62025
33.3%
e 62025
33.3%
Other Punctuation
ValueCountFrequency (%)
. 71143
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 62025
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6710992
96.4%
Latin 248100
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1196111
17.8%
1 1178521
17.6%
3 925378
13.8%
0 576376
8.6%
4 558149
8.3%
9 482269
7.2%
6 473328
 
7.1%
8 445869
 
6.6%
5 426891
 
6.4%
7 376957
 
5.6%
Latin
ValueCountFrequency (%)
N 62025
25.0%
o 62025
25.0%
n 62025
25.0%
e 62025
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6959092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1196111
17.2%
1 1178521
16.9%
3 925378
13.3%
0 576376
8.3%
4 558149
8.0%
9 482269
6.9%
6 473328
 
6.8%
8 445869
 
6.4%
5 426891
 
6.1%
7 376957
 
5.4%
Other values (5) 319243
 
4.6%

Supervisor District
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size46.7 MiB
Distinct42
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
Tenderloin
825200 
South of Market
595340 
Mission
552610 
Financial District/South Beach
408832 
Bayview Hunters Point
 
332334
Other values (37)
3411182 

Length

Max length30
Median length18
Mean length13.834863
Min length4

Characters and Unicode

Total characters84745426
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHayes Valley
2nd rowPotrero Hill
3rd rowMission
4th rowTenderloin
5th rowRussian Hill

Common Values

ValueCountFrequency (%)
Tenderloin 825200
 
13.5%
South of Market 595340
 
9.7%
Mission 552610
 
9.0%
Financial District/South Beach 408832
 
6.7%
Bayview Hunters Point 332334
 
5.4%
Sunset/Parkside 237680
 
3.9%
Western Addition 227221
 
3.7%
Nob Hill 202670
 
3.3%
Outer Richmond 162570
 
2.7%
Hayes Valley 151651
 
2.5%
Other values (32) 2429390
39.7%

Length

2023-02-21T23:28:22.630301image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tenderloin 825200
 
7.1%
market 742197
 
6.4%
of 729551
 
6.3%
mission 716314
 
6.2%
south 595340
 
5.1%
beach 537047
 
4.6%
hill 409163
 
3.5%
financial 408832
 
3.5%
district/south 408832
 
3.5%
bayview 332334
 
2.9%
Other values (47) 5866144
50.7%

Most occurring characters

ValueCountFrequency (%)
i 7833804
 
9.2%
e 7727960
 
9.1%
n 6723063
 
7.9%
o 5720858
 
6.8%
t 5603871
 
6.6%
5445456
 
6.4%
a 5005782
 
5.9%
r 4780317
 
5.6%
s 4689334
 
5.5%
l 3150657
 
3.7%
Other values (36) 28064324
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66227785
78.1%
Uppercase Letter 12034136
 
14.2%
Space Separator 5445456
 
6.4%
Other Punctuation 1038049
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 7833804
11.8%
e 7727960
11.7%
n 6723063
10.2%
o 5720858
8.6%
t 5603871
8.5%
a 5005782
7.6%
r 4780317
 
7.2%
s 4689334
 
7.1%
l 3150657
 
4.8%
h 2610956
 
3.9%
Other values (13) 12381183
18.7%
Uppercase Letter
ValueCountFrequency (%)
M 1743694
14.5%
S 1422747
11.8%
H 1280893
10.6%
P 1193611
9.9%
B 1059553
8.8%
T 1036903
 
8.6%
F 482648
 
4.0%
N 414216
 
3.4%
D 408832
 
3.4%
V 375085
 
3.1%
Other values (11) 2615954
21.7%
Space Separator
ValueCountFrequency (%)
5445456
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1038049
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 78261921
92.3%
Common 6483505
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 7833804
 
10.0%
e 7727960
 
9.9%
n 6723063
 
8.6%
o 5720858
 
7.3%
t 5603871
 
7.2%
a 5005782
 
6.4%
r 4780317
 
6.1%
s 4689334
 
6.0%
l 3150657
 
4.0%
h 2610956
 
3.3%
Other values (34) 24415319
31.2%
Common
ValueCountFrequency (%)
5445456
84.0%
/ 1038049
 
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84745426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 7833804
 
9.2%
e 7727960
 
9.1%
n 6723063
 
7.9%
o 5720858
 
6.8%
t 5603871
 
6.6%
5445456
 
6.4%
a 5005782
 
5.9%
r 4780317
 
5.6%
s 4689334
 
5.5%
l 3150657
 
3.7%
Other values (36) 28064324
33.1%

RowID
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct6125498
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size46.7 MiB
221210313-E36
 
1
140040033-RC1
 
1
140710227-E07
 
1
140400396-B01
 
1
133450164-KM14
 
1
Other values (6125493)
6125493 

Length

Max length16
Median length13
Mean length12.877684
Min length12

Characters and Unicode

Total characters78882225
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6125498 ?
Unique (%)100.0%

Sample

1st row221210313-E36
2nd row220190150-E29
3rd row211233271-T07
4th row212933533-B02
5th row221202543-E41

Common Values

ValueCountFrequency (%)
221210313-E36 1
 
< 0.1%
140040033-RC1 1
 
< 0.1%
140710227-E07 1
 
< 0.1%
140400396-B01 1
 
< 0.1%
133450164-KM14 1
 
< 0.1%
133350354-55 1
 
< 0.1%
133480259-AM12 1
 
< 0.1%
133220341-E36 1
 
< 0.1%
140730131-52 1
 
< 0.1%
140250005-E12 1
 
< 0.1%
Other values (6125488) 6125488
> 99.9%

Length

2023-02-21T23:28:23.058602image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
221210313-e36 1
 
< 0.1%
220181524-e08 1
 
< 0.1%
211232439-b01 1
 
< 0.1%
211942517-t03 1
 
< 0.1%
212932758-b01 1
 
< 0.1%
221201816-t03 1
 
< 0.1%
211941580-scrt4 1
 
< 0.1%
220181779-50 1
 
< 0.1%
210390329-t07 1
 
< 0.1%
220111608-e06 1
 
< 0.1%
Other values (6125488) 6125488
> 99.9%

Most occurring characters

ValueCountFrequency (%)
0 14663213
18.6%
1 11882383
15.1%
2 9021698
11.4%
3 7276307
9.2%
- 6125498
7.8%
4 4375905
 
5.5%
5 4104729
 
5.2%
6 4100249
 
5.2%
8 4049933
 
5.1%
7 3928245
 
5.0%
Other values (28) 9354065
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67022671
85.0%
Dash Punctuation 6125498
 
7.8%
Uppercase Letter 5734050
 
7.3%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2288851
39.9%
M 949867
16.6%
T 676980
 
11.8%
B 412910
 
7.2%
R 405379
 
7.1%
K 242935
 
4.2%
C 237877
 
4.1%
A 218820
 
3.8%
S 148782
 
2.6%
D 43291
 
0.8%
Other values (15) 108358
 
1.9%
Decimal Number
ValueCountFrequency (%)
0 14663213
21.9%
1 11882383
17.7%
2 9021698
13.5%
3 7276307
10.9%
4 4375905
 
6.5%
5 4104729
 
6.1%
6 4100249
 
6.1%
8 4049933
 
6.0%
7 3928245
 
5.9%
9 3620009
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
p 3
50.0%
x 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 6125498
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73148169
92.7%
Latin 5734056
 
7.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2288851
39.9%
M 949867
16.6%
T 676980
 
11.8%
B 412910
 
7.2%
R 405379
 
7.1%
K 242935
 
4.2%
C 237877
 
4.1%
A 218820
 
3.8%
S 148782
 
2.6%
D 43291
 
0.8%
Other values (17) 108364
 
1.9%
Common
ValueCountFrequency (%)
0 14663213
20.0%
1 11882383
16.2%
2 9021698
12.3%
3 7276307
9.9%
- 6125498
8.4%
4 4375905
 
6.0%
5 4104729
 
5.6%
6 4100249
 
5.6%
8 4049933
 
5.5%
7 3928245
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78882225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14663213
18.6%
1 11882383
15.1%
2 9021698
11.4%
3 7276307
9.2%
- 6125498
7.8%
4 4375905
 
5.5%
5 4104729
 
5.2%
6 4100249
 
5.2%
8 4049933
 
5.1%
7 3928245
 
5.0%
Other values (28) 9354065
11.9%

case_location
Categorical

Distinct107102
Distinct (%)1.7%
Missing952
Missing (%)< 0.1%
Memory size46.7 MiB
POINT (-122.39998111124 37.777624238929)
 
19431
POINT (-122.419854245692 37.786117211838)
 
17419
POINT (-122.409026046516 37.78114586126)
 
14195
POINT (-122.409853729941 37.783386237938)
 
14006
POINT (-122.411784369455 37.784091036176)
 
13080
Other values (107097)
6046415 

Length

Max length46
Median length41
Mean length41.608154
Min length36

Characters and Unicode

Total characters254831055
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10732 ?
Unique (%)0.2%

Sample

1st rowPOINT (-122.42316555403964 37.77781524520032)
2nd rowPOINT (-122.39469970274361 37.76460987856451)
3rd rowPOINT (-122.42057572093252 37.76418194637148)
4th rowPOINT (-122.41243514072728 37.78347684038771)
5th rowPOINT (-122.4233369425531 37.799534868680034)

Common Values

ValueCountFrequency (%)
POINT (-122.39998111124 37.777624238929) 19431
 
0.3%
POINT (-122.419854245692 37.786117211838) 17419
 
0.3%
POINT (-122.409026046516 37.78114586126) 14195
 
0.2%
POINT (-122.409853729941 37.783386237938) 14006
 
0.2%
POINT (-122.411784369455 37.784091036176) 13080
 
0.2%
POINT (-122.411971890566 37.785024660689) 12164
 
0.2%
POINT (-122.384094238098 37.616882323925) 11036
 
0.2%
POINT (-122.412596970637 37.781119212154) 10112
 
0.2%
POINT (-122.419668973861 37.765051338195) 9625
 
0.2%
POINT (-122.409518341416 37.781537433122) 9482
 
0.2%
Other values (107092) 5993996
97.9%

Length

2023-02-21T23:28:23.230684image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
point 6124546
33.3%
122.39998111124 19433
 
0.1%
37.777624238929 19431
 
0.1%
122.419854245692 17419
 
0.1%
37.786117211838 17419
 
0.1%
122.411784369455 14320
 
0.1%
122.409026046516 14195
 
0.1%
37.78114586126 14195
 
0.1%
122.409853729941 14006
 
0.1%
37.783386237938 14006
 
0.1%
Other values (209147) 12104668
65.9%

Most occurring characters

ValueCountFrequency (%)
2 26349084
 
10.3%
7 25812667
 
10.1%
1 20933529
 
8.2%
3 20356681
 
8.0%
4 18878845
 
7.4%
8 15222441
 
6.0%
6 13859990
 
5.4%
9 13803494
 
5.4%
5 13243681
 
5.2%
0 12876091
 
5.1%
Other values (10) 73494552
28.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 181336503
71.2%
Uppercase Letter 30622730
 
12.0%
Other Punctuation 12249092
 
4.8%
Space Separator 12249092
 
4.8%
Dash Punctuation 6124546
 
2.4%
Open Punctuation 6124546
 
2.4%
Close Punctuation 6124546
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 26349084
14.5%
7 25812667
14.2%
1 20933529
11.5%
3 20356681
11.2%
4 18878845
10.4%
8 15222441
8.4%
6 13859990
7.6%
9 13803494
7.6%
5 13243681
7.3%
0 12876091
7.1%
Uppercase Letter
ValueCountFrequency (%)
O 6124546
20.0%
T 6124546
20.0%
N 6124546
20.0%
I 6124546
20.0%
P 6124546
20.0%
Other Punctuation
ValueCountFrequency (%)
. 12249092
100.0%
Space Separator
ValueCountFrequency (%)
12249092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6124546
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6124546
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6124546
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 224208325
88.0%
Latin 30622730
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 26349084
11.8%
7 25812667
11.5%
1 20933529
9.3%
3 20356681
9.1%
4 18878845
8.4%
8 15222441
 
6.8%
6 13859990
 
6.2%
9 13803494
 
6.2%
5 13243681
 
5.9%
0 12876091
 
5.7%
Other values (5) 42871822
19.1%
Latin
ValueCountFrequency (%)
O 6124546
20.0%
T 6124546
20.0%
N 6124546
20.0%
I 6124546
20.0%
P 6124546
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 254831055
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 26349084
 
10.3%
7 25812667
 
10.1%
1 20933529
 
8.2%
3 20356681
 
8.0%
4 18878845
 
7.4%
8 15222441
 
6.0%
6 13859990
 
5.4%
9 13803494
 
5.4%
5 13243681
 
5.2%
0 12876091
 
5.1%
Other values (10) 73494552
28.8%

Analysis Neighborhoods
Real number (ℝ)

Distinct41
Distinct (%)< 0.1%
Missing17785
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean22.559159
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 MiB
2023-02-21T23:28:23.325635image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19
median23
Q335
95-th percentile39
Maximum41
Range40
Interquartile range (IQR)26

Descriptive statistics

Standard deviation12.683821
Coefficient of variation (CV)0.56224705
Kurtosis-1.3469541
Mean22.559159
Median Absolute Deviation (MAD)12
Skewness-0.26537366
Sum1.3778487 × 108
Variance160.87931
MonotonicityNot monotonic
2023-02-21T23:28:23.388039image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
36 825085
 
13.5%
34 595252
 
9.7%
20 585113
 
9.6%
8 408824
 
6.7%
1 332298
 
5.4%
35 237666
 
3.9%
39 227189
 
3.7%
21 202649
 
3.3%
29 162567
 
2.7%
9 151641
 
2.5%
Other values (31) 2379429
38.8%
ValueCountFrequency (%)
1 332298
5.4%
2 115658
 
1.9%
3 91234
 
1.5%
4 74452
 
1.2%
5 146848
 
2.4%
6 125288
 
2.0%
7 123004
 
2.0%
8 408824
6.7%
9 151641
 
2.5%
10 29510
 
0.5%
ValueCountFrequency (%)
41 134210
 
2.2%
40 78468
 
1.3%
39 227189
 
3.7%
38 36146
 
0.6%
37 41335
 
0.7%
36 825085
13.5%
35 237666
 
3.9%
34 595252
9.7%
33 10263
 
0.2%
32 94631
 
1.5%

Interactions

2023-02-21T23:25:29.411734image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:24:57.716416image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:05.623260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:13.508298image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:21.604297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:31.061265image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:24:59.318089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:07.085173image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:15.201581image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:23.225909image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:32.755610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:00.945819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:08.631169image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:16.865194image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:24.737722image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:34.373351image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:02.513278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:10.204427image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:18.452835image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:26.206472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:36.029857image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:04.154744image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:11.846753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:20.048298image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-21T23:25:27.792071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-02-21T23:28:23.530023image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Call NumberIncident NumberZipcode of IncidentUnit sequence in call dispatchAnalysis NeighborhoodsCall TypeCall Final DispositionCityBattalionOriginal PriorityPriorityFinal PriorityALS UnitCall Type GroupNumber of AlarmsUnit TypeFire Prevention DistrictNeighborhooods - Analysis Boundaries
Call Number1.0001.000-0.023-0.0350.0130.0570.2610.3370.0250.1480.1000.1670.1130.0360.0180.0860.1050.030
Incident Number1.0001.000-0.023-0.0350.0130.0570.2610.3350.0260.1500.1000.1670.1120.0360.0180.0860.1050.030
Zipcode of Incident-0.023-0.0231.0000.039-0.2730.0630.0360.2380.5360.0220.0140.0300.0470.0640.0140.0380.5730.795
Unit sequence in call dispatch-0.035-0.0350.0391.000-0.0140.0810.0260.0130.0140.0160.0160.0420.0430.1580.4080.0500.0130.016
Analysis Neighborhoods0.0130.013-0.273-0.0141.0000.0620.0350.0850.4600.0240.0170.0400.0720.0790.0140.0400.4640.995
Call Type0.0570.0570.0630.0810.0621.0000.1900.0940.0790.1450.1450.3350.3980.7220.0800.2520.0680.087
Call Final Disposition0.2610.2610.0360.0260.0350.1901.0000.1990.0300.1780.1660.3690.2800.5120.0260.2090.0410.045
City0.3370.3350.2380.0130.0850.0940.1991.0000.2500.1190.0840.1360.0540.0570.0210.2130.1940.281
Battalion0.0250.0260.5360.0140.4600.0790.0300.2501.0000.0260.0180.0380.0870.0910.0150.0570.7410.673
Original Priority0.1480.1500.0220.0160.0240.1450.1780.1190.0261.0000.5210.8490.1530.3920.0170.1770.0300.034
Priority0.1000.1000.0140.0160.0170.1450.1660.0840.0180.5211.0001.0000.1550.4360.0170.1820.0190.026
Final Priority0.1670.1670.0300.0420.0400.3350.3690.1360.0380.8491.0001.0000.1330.7270.0310.3970.0390.055
ALS Unit0.1130.1120.0470.0430.0720.3980.2800.0540.0870.1530.1550.1331.0000.3510.0310.7650.0950.123
Call Type Group0.0360.0360.0640.1580.0790.7220.5120.0570.0910.3920.4360.7270.3511.0000.1280.4070.0810.117
Number of Alarms0.0180.0180.0140.4080.0140.0800.0260.0210.0150.0170.0170.0310.0310.1281.0000.0420.0160.022
Unit Type0.0860.0860.0380.0500.0400.2520.2090.2130.0570.1770.1820.3970.7650.4070.0421.0000.1030.186
Fire Prevention District0.1050.1050.5730.0130.4640.0680.0410.1940.7410.0300.0190.0390.0950.0810.0160.1031.0000.585
Neighborhooods - Analysis Boundaries0.0300.0300.7950.0160.9950.0870.0450.2810.6730.0340.0260.0550.1230.1170.0220.1860.5851.000

Missing values

2023-02-21T23:25:52.483100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-21T23:26:26.212741image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-02-21T23:27:36.728147image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Call NumberUnit IDIncident NumberCall TypeCall DateWatch DateReceived DtTmEntry DtTmDispatch DtTmResponse DtTmOn Scene DtTmTransport DtTmHospital DtTmCall Final DispositionAvailable DtTmAddressCityZipcode of IncidentBattalionStation AreaBoxOriginal PriorityPriorityFinal PriorityALS UnitCall Type GroupNumber of AlarmsUnit TypeUnit sequence in call dispatchFire Prevention DistrictSupervisor DistrictNeighborhooods - Analysis BoundariesRowIDcase_locationAnalysis Neighborhoods
0221210313E3622054955Outside Fire05/01/202204/30/202205/01/2022 02:58:25 AM05/01/2022 02:59:15 AM05/01/2022 02:59:25 AM05/01/2022 03:01:06 AM05/01/2022 03:02:27 AMNaNNaNFire05/01/2022 03:05:00 AMGOUGH ST/GROVE STSan Francisco94102.0B0236.03265333TrueFire1ENGINE1.025Hayes Valley221210313-E36POINT (-122.42316555403964 37.77781524520032)9.0
1220190150E2922008871Alarms01/19/202201/18/202201/19/2022 01:42:12 AM01/19/2022 01:44:13 AM01/19/2022 01:44:28 AM01/19/2022 01:46:47 AM01/19/2022 01:49:32 AMNaNNaNFire01/19/2022 02:35:26 AM100 Block of MISSISSIPPI STSan Francisco94107.0B0329.02431333TrueAlarm1ENGINE1.0310Potrero Hill220190150-E29POINT (-122.39469970274361 37.76460987856451)26.0
2211233271T0721053032Alarms05/03/202105/03/202105/03/2021 09:28:12 PM05/03/2021 09:28:12 PM05/03/2021 09:28:17 PM05/03/2021 09:29:10 PM05/03/2021 09:32:15 PMNaNNaNFire05/03/2021 09:38:09 PM0 Block of HOFF STSan Francisco94110.0B027.05236A33FalseAlarm1TRUCK2.029Mission211233271-T07POINT (-122.42057572093252 37.76418194637148)20.0
3212933533B0221127914Alarms10/20/202110/20/202110/20/2021 10:08:47 PM10/20/2021 10:09:53 PM10/20/2021 10:10:07 PM10/20/2021 10:11:55 PMNaNNaNNaNFire10/20/2021 10:25:52 PM200 Block of JONES STSan Francisco94102.0B033.01456333FalseAlarm1CHIEF3.036Tenderloin212933533-B02POINT (-122.41243514072728 37.78347684038771)36.0
4221202543E4122054815Alarms04/30/202204/30/202204/30/2022 06:35:58 PM04/30/2022 06:37:28 PM04/30/2022 06:37:43 PM04/30/2022 06:38:17 PMNaNNaNNaNFire04/30/2022 06:40:08 PM1400 Block of FILBERT STSan Francisco94109.0B0416.03146333FalseAlarm1ENGINE4.042Russian Hill221202543-E41POINT (-122.4233369425531 37.799534868680034)32.0
5211232439B0121052945Alarms05/03/202105/03/202105/03/2021 04:57:21 PM05/03/2021 04:58:39 PM05/03/2021 04:58:44 PM05/03/2021 05:00:27 PMNaNNaNNaNFire05/03/2021 05:05:20 PM500 Block of JONES STSan Francisco94102.0B013.01462333FalseAlarm1CHIEF2.016Tenderloin211232439-B01POINT (-122.41299723589606 37.78626844171642)36.0
6211942517T0321083057Alarms07/13/202107/13/202107/13/2021 04:50:10 PM07/13/2021 04:51:07 PM07/13/2021 04:51:17 PMNaNNaNNaNNaNFire07/13/2021 04:54:45 PM900 Block of VAN NESS AVESan Francisco94109.0B043.03162333FalseAlarm1TRUCK3.026Tenderloin211942517-T03POINT (-122.42090696864193 37.784067668377766)36.0
7212932758B0121127810Alarms10/20/202110/20/202110/20/2021 05:46:09 PM10/20/2021 05:47:57 PM10/20/2021 05:48:05 PM10/20/2021 05:49:54 PM10/20/2021 05:53:45 PMNaNNaNFire10/20/2021 06:00:04 PM0 Block of BEACH STSan Francisco94133.0B0128.00939333FalseAlarm1CHIEF2.013North Beach212932758-B01POINT (-122.40987728293031 37.808050096906186)23.0
8221201816T0322054719Structure Fire04/30/202204/30/202204/30/2022 02:27:39 PM04/30/2022 02:28:53 PM04/30/2022 02:29:13 PM04/30/2022 02:31:58 PM04/30/2022 02:31:58 PMNaNNaNFire04/30/2022 02:46:15 PMMISSION ST/9TH STSan Francisco94103.0B0236.02336333FalseAlarm1TRUCK3.026South of Market221201816-T03POINT (-122.41471100467277 37.77623051778801)34.0
9211941580SCRT421082970Medical Incident07/13/202107/13/202107/13/2021 12:23:31 PM07/13/2021 12:28:02 PM07/13/2021 12:47:21 PM07/13/2021 12:47:21 PMNaNNaNNaNSFPD07/13/2021 12:48:46 PM100 Block of VICENTE STSan Francisco94127.0B0839.08612112FalseNon Life-threatening1SUPPORT1.087West of Twin Peaks211941580-SCRT4POINT (-122.46750730609165 37.73983589352891)41.0
Call NumberUnit IDIncident NumberCall TypeCall DateWatch DateReceived DtTmEntry DtTmDispatch DtTmResponse DtTmOn Scene DtTmTransport DtTmHospital DtTmCall Final DispositionAvailable DtTmAddressCityZipcode of IncidentBattalionStation AreaBoxOriginal PriorityPriorityFinal PriorityALS UnitCall Type GroupNumber of AlarmsUnit TypeUnit sequence in call dispatchFire Prevention DistrictSupervisor DistrictNeighborhooods - Analysis BoundariesRowIDcase_locationAnalysis Neighborhoods
6125488230180016SWRT523008573Medical Incident01/18/202301/17/202301/18/2023 12:08:41 AM01/18/2023 12:11:13 AM01/18/2023 12:46:14 AM01/18/2023 12:46:53 AM01/18/2023 01:00:30 AMNaNNaNOther01/18/2023 01:17:45 AM2000 Block of MCALLISTER STSan Francisco94117.0B05214362112FalseNon Life-threatening1SUPPORT1.055Lone Mountain/USF230180016-SWRT5POINT (-122.4458022818456 37.77679542256278)18.0
6125489230180010E3623008572Outside Fire01/18/202301/17/202301/18/2023 12:07:07 AM01/18/2023 12:09:18 AM01/18/2023 12:09:32 AM01/18/2023 12:11:14 AM01/18/2023 12:14:08 AMNaNNaNFire01/18/2023 12:15:17 AMMISSION ST/9TH STSan Francisco94103.0B02362336333TrueFire1ENGINE1.026South of Market230180010-E36POINT (-122.41471100467277 37.77623051778801)34.0
6125490230180004RC323008571Medical Incident01/18/202301/17/202301/18/2023 12:06:06 AM01/18/2023 12:07:09 AM01/18/2023 12:07:37 AM01/18/2023 12:10:14 AMNaNNaNNaNCode 2 Transport01/18/2023 12:16:07 AM100 Block of 6TH STSan Francisco94103.0B0312251EE3TruePotentially Life-Threatening1RESCUE CAPTAIN3.036South of Market230180004-RC3POINT (-122.40848372232699 37.7807144867661)34.0
6125491230320152T1223015355Alarms02/01/202301/31/202302/01/2023 01:40:47 AM02/01/2023 01:43:53 AM02/01/2023 01:44:11 AM02/01/2023 01:46:47 AMNaNNaNNaNFire02/01/2023 01:49:32 AM400 Block of PARNASSUS AVESan Francisco94131.0B05125155333FalseAlarm1TRUCK3.057Inner Sunset230320152-T12POINT (-122.45820598858694 37.763316596988)14.0
6125492230320097B0223015343Alarms02/01/202301/31/202302/01/2023 01:04:25 AM02/01/2023 01:05:44 AM02/01/2023 01:06:16 AM02/01/2023 01:09:06 AM02/01/2023 01:12:34 AMNaNNaNFire02/01/2023 01:16:58 AM0 Block of TURK STSan Francisco94102.0B0311365333FalseAlarm1CHIEF2.036Tenderloin230320097-B02POINT (-122.40985372994083 37.78338623793843)36.0
6125493230313450T1523015313Alarms01/31/202301/31/202301/31/2023 11:16:58 PM01/31/2023 11:18:48 PM01/31/2023 11:19:07 PM01/31/2023 11:21:36 PM01/31/2023 11:22:46 PMNaNNaNFire01/31/2023 11:29:54 PM700 Block of DELANO AVSan Francisco94112.0B0915833333FalseAlarm1TRUCK2.09.011Outer Mission230313450-T15POINT (-122.44530628839591 37.71979945661107)28.0
6125494230320055AM24423015335Medical Incident02/01/202301/31/202302/01/2023 12:31:02 AM02/01/2023 12:34:27 AM02/01/2023 12:36:23 AM02/01/2023 12:36:45 AM02/01/2023 12:44:31 AMNaNNaNOther02/01/2023 01:07:05 AM800 Block of TURK STSan Francisco94102.0B0253216233FalseNon Life-threatening1PRIVATE1.025Western Addition230320055-AM244POINT (-122.42309018884103 37.78158540310524)39.0
6125495230181881QRV123008833Medical Incident01/18/202301/18/202301/18/2023 02:40:21 PM01/18/2023 02:40:53 PM01/18/2023 02:41:07 PM01/18/2023 02:41:09 PM01/18/2023 02:44:56 PMNaNNaNNo Merit01/18/2023 02:48:21 PM800 Block of MARKET STSan Francisco94103.0B03131322333TruePotentially Life-Threatening1SUPPORT1.036South of Market230181881-QRV1POINT (-122.40649776780393 37.785081174265976)34.0
6125496230181881AM10823008833Medical Incident01/18/202301/18/202301/18/2023 02:40:21 PM01/18/2023 02:40:53 PM01/18/2023 02:41:07 PM01/18/2023 02:41:31 PM01/18/2023 02:47:41 PMNaNNaNNo Merit01/18/2023 02:50:33 PM800 Block of MARKET STSan Francisco94103.0B03131322333FalsePotentially Life-Threatening1PRIVATE2.036South of Market230181881-AM108POINT (-122.40649776780393 37.785081174265976)34.0
6125497230180743SCRT323008682Medical Incident01/18/202301/18/202301/18/2023 08:58:16 AM01/18/2023 09:04:06 AM01/18/2023 09:05:36 AM01/18/2023 09:05:43 AM01/18/2023 09:40:48 AMNaNNaNOther01/18/2023 10:15:48 AM700 Block of 7TH AVESan Francisco94118.0B07292275112FalseNon Life-threatening1SUPPORT1.071Inner Richmond230180743-SCRT3POINT (-122.46494596679975 37.77440174620704)11.0